Snowflake OverviewUNIXBusinessApplication

Snowflake is the #1 ranked solution in top Data Warehouse tools and top Cloud Data Warehouse tools. PeerSpot users give Snowflake an average rating of 8.4 out of 10. Snowflake is most commonly compared to Microsoft Azure Synapse Analytics: Snowflake vs Microsoft Azure Synapse Analytics. Snowflake is popular among the large enterprise segment, accounting for 69% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a computer software company, accounting for 18% of all views.
Snowflake Buyer's Guide

Download the Snowflake Buyer's Guide including reviews and more. Updated: November 2022

What is Snowflake?

Snowflake is a fully managed SaaS (software as a service) that provides a single platform for data warehousing, data lakes, data engineering, data science, data application development, and secure sharing and consumption of real-time / shared data.

Its platform is made up of three components:

  1. Cloud services: As part of its cloud services, Snowflake uses ANSI SQL, which empowers users to optimize their data and manage their infrastructure, while Snowflake handles the security and encryption of stored data.
  1. Query processing: With Snowflake, workload concurrency is never a problem because its compute layer is made up of virtual cloud data warehouses that let you analyze data through requests. Each of the warehouses do not compete for computing resources nor do they affect the performance of each other.
  1. Database storage: Snowflake manages all parts of the data storage process automatically, including file size, compression, organization, structure, and metadata, as well as statistics.

Snowflake Features

Snowflake has many valuable key features. Some of the most useful ones include:

  • Scalability: Snowflake architecture provides nearly unlimited scalability and high speed because it uses a single elastic performance engine. The solution also supports an unlimited amount of concurrent users and workloads, from interactive to batch.
  • Automation: Snowflake makes automation easy and enables enterprises to automate data management, security, governance, availability, and data resiliency.
  • Seamless cross-cloud and cross-region connections: With seamless cross-cloud and cross-region connections, Snowflake eliminates ETL and data silos. Anyone who needs access to shared secure data can get a single copy via the data cloud. In addition, Snowflake makes remote collaboration and decision-making fast and easy via a single shared data source.
  • Third-party data integrations: Snowflake’s Data Marketplace offers third-party data which allows you to connect with Snowflake customers to extend workflows with data services and third-party applications.

Snowflake Benefits

There are many benefits to implementing Snowflake. Some of the biggest advantages the solution offers include:

  • Helps optimize costs
  • Reduces downtime
  • Improves operational efficiency
  • Built for high reliability and availability
  • Automates data replication for fast recovery

Reviews from Real Users

Below are some reviews and helpful feedback written by PeerSpot users currently using the Snowflake solution.

Sreenivasan R., Director of Data Architecture and Engineering at Decision Minds, says, "Data sharing is a good feature. It is a majorly used feature. The elastic compute is another big feature. Separating compute and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not really doing any performance tuning, and the entire burden of performance tuning and SQL tuning is on Snowflake. Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake."

A director of business operations at a logistics company mentions, "It requires no maintenance on our part. They handle all that. The speed is phenomenal. The pricing isn't really anything more than what you would be paying for a SQL server license or another tool to execute the same thing. We have zero maintenance on our side to do anything and the speed at which it performs queries and loads the data is amazing. It handles unstructured data extremely well, too. So, if the data is in a JSON array or an XML, it handles that super well."

A Solution Architect at a wholesaler/distributor comments, "The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities. There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business."

Snowflake was previously known as Snowflake Computing.

Snowflake Customers

Accordant Media, Adobe, Kixeye Inc., Revana, SOASTA, White Ops

Snowflake Video

Snowflake Pricing Advice

What users are saying about Snowflake pricing:
  • "Snowflake goes by credits. For a financial institution where you have 5,000 employees, monthly costs may run up to maybe $5,000 to $6,000. This is actually based on the usage. It is mostly the compute cost. Your computing cost is the variable that is actually based on your usage. It is pay-per-use. In a pay-per-use case, you won't be spending more than $6,000 to $7,000 a month. It is not more than that for a small or medium enterprise, and it may come down to $100K per year. Storage is very standard, which is $23 a terabyte. It is not much for any enterprise. If you have even 20 terabytes, you are not spending more than $400 per month, which may turn out to be $2,000 to $3,000 per annum."
  • "There is a separation of storage and compute, so you only pay for what you use."
  • "It is hard to say because we're usually engaged in the transition as opposed to the long term. Their storage costs are easily within pennies of what AWS S3 would normally cost. Most of the clients I've been working with are in the financial sector, and they're relatively small. I would put them in an SMB connection. The first thing we have to bring up for people is that they're going to build this. They shouldn't store their data in S3. They should pipeline directly into Snowflake and use it on their storage. So, the cost is a big issue because these are small to medium size companies, and that is the biggest thing we had to price point for them."
  • Snowflake Reviews

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    SreenivasanRamanujam - PeerSpot reviewer
    Director -Data Architecture and Engineering at Decision Minds
    Real User
    Top 10
    Good usability, good data sharing and elastic compute features, and requires less DBA involvement
    Pros and Cons
    • "Data sharing is a good feature. It is a majorly used feature. The elastic compute is another big feature. Separating compute and storage gives you flexibility. It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not really doing any performance tuning, and the entire burden of performance tuning and SQL tuning is on Snowflake. Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake."
    • "Portability is a big hurdle right now for our clients. Porting all of your existing SQL ecosystem, such as stored procedures, to Snowflake is a major pain point. Currently, Snowflake stored procedures use JavaScript, but they should support SQL-based stored procedures. It would be a huge advantage if you can write your stored procedures using SQL. It seems that they are working on this feature, and they are yet to release it. I remember seeing some notes saying that they were going to do that in the future, but the sooner this feature comes out, it would be better for Snowflake because there are a lot of clients with whom I'm interacting, and their main hurdle is to take their existing Oracle or SQL Server stored procedures and move them into Snowflake. For this, you need to learn JavaScript and how it works, which is not easy and becomes a little tricky. If it supports SQL-based procedures, then you can just cut-paste the SQL code, run it, and easily fix small issues."

    What is our primary use case?

    For Snowflake, we had four main use cases. The first use case was related to a data warehouse, and my banking client wanted to move his SQL Server database to Snowflake. All the source systems were also on Oracle and file-based systems, and the target data warehouse was SQL Server. From SQL Server, the client wanted to move to Snowflake. 

    The second use case was related to a chat or messaging client. They were using EMR Hadoop as their data warehouse, but it was not performing, so we had to move the EMR Hadoop to Snowflake. 

    The third use case was related to a ServiceNow compliance system, where ServiceNow was using SAP HANA for its reporting data warehouse, but it was too slow. It was not performing, and it was causing a lot of problems. We moved that ServiceNow compliance system from SAP HANA to Snowflake.

    The fourth use case was related to a huge SQL Server database for a banking client. We moved the entire SQL database to Snowflake. 

    What is most valuable?

    Data sharing is a good feature. It is a majorly used feature. The elastic compute is another big feature. Separating compute and storage gives you flexibility. 

    It doesn't require much DBA involvement because it doesn't need any performance tuning. We are not really doing any performance tuning, and the entire burden of performance tuning and SQL tuning is on Snowflake.

    Its usability is very good. I don't need to ramp up any user, and its onboarding is easier. You just onboard the user, and you are done with it. There are simple SQL and UI, and people are able to use this solution easily. Ease of use is a big thing in Snowflake.

    What needs improvement?

    Portability is a big hurdle right now for our clients. Porting all of your existing SQL ecosystem, such as stored procedures, to Snowflake is a major pain point. Currently, Snowflake stored procedures use JavaScript, but they should support SQL-based stored procedures. It would be a huge advantage if you can write your stored procedures using SQL. 

    It seems that they are working on this feature, and they are yet to release it. I remember seeing some notes saying that they were going to do that in the future, but the sooner this feature comes out, it would be better for Snowflake because there are a lot of clients with whom I'm interacting, and their main hurdle is to take their existing Oracle or SQL Server stored procedures and move them into Snowflake. For this, you need to learn JavaScript and how it works, which is not easy and becomes a little tricky. If it supports SQL-based procedures, then you can just cut-paste the SQL code, run it, and easily fix small issues. 

    For how long have I used the solution?

    I have been using this solution for three years.

    Buyer's Guide
    Snowflake
    November 2022
    Learn what your peers think about Snowflake. Get advice and tips from experienced pros sharing their opinions. Updated: November 2022.
    656,862 professionals have used our research since 2012.

    What do I think about the stability of the solution?

    So far, with all four clients who have this solution, I have not seen any problem that stands out and causes major headaches or something like that.

    What do I think about the scalability of the solution?

    Its scalability is really good. You can scale in both ways. You can actually scale up and down or scale out. Scaling up and down is done where we have an extra small warehouse, and we are moving to small, medium, large, or something like that. If you have a query that is running slow or a lot of data you are dealing with is slow, you can scale up. If you want to scale down from large to small, you can do that. 

    If you want to get concurrency, scale-out architecture is available. I can actually do a cluster-based architecture where I can have two clusters, three clusters, or something like that. This way the concurrency can be improved.

    In terms of the number of users, we have around 200 users.

    How are customer service and support?

    They have a website where you have to go and raise your tickets. They resolve the ticket, and they are working fine. 

    They don't actually entertain emails nowadays because the company has become big. I remember initially interacting with them through email. Now they don't do that. They clearly say not to send emails and go through the ticketing process, which makes sense. For a big company, it is not possible to track emails.

    How was the initial setup?

    It is not complex. It is straightforward. It is a very simple database anyway. It is just having a script and running them. 

    The only thing is that you have to go through the whole nine yards of getting an account or getting your single sign-on enabled. That is a part of every process. For any single sign-on application, you will have to go through this process. 

    You also need to involve the right people, such as the security team, infrastructure team, and networking team. When they are there, the setup becomes easier, and there are no problems.

    For its maintenance, we have only two or three people. We have one DBA and one account admin. There is another DBA who will take a rotation. You don't really need a big team to manage this because it is all cloud. Management is not that heavy.

    What's my experience with pricing, setup cost, and licensing?

    Snowflake goes by credits. For a financial institution where you have 5,000 employees, monthly costs may run up to maybe $5,000 to $6,000. This is actually based on the usage. It is mostly the compute cost. Your computing cost is the variable that is actually based on your usage. It is pay-per-use. In a pay-per-use case, you won't be spending more than $6,000 to $7,000 a month. It is not more than that for a small or medium enterprise, and it may come down to $100K per year.

    Storage is very standard, which is $23 a terabyte. It is not much for any enterprise. If you have even 20 terabytes, you are not spending more than $400 per month, which may turn out to be $2,000 to $3,000 per annum. 

    Which other solutions did I evaluate?

    When comparing it with SAP HANA, there is no one solution that fits all. Snowflake is useful if you have a SaaS-based product such as Salesforce, Workday, Anaplan, and Greenhouse. You can get the data from this type of SaaS-based system and ingest data.

    SAP is born out of the entire ERP ecosystem. You have enterprise resource planning, and you have manufacturing, finance, and other systems. Big manufacturing industries usually implement ERPs because they want to do reporting, etc. SAP has this custom box stuff, and it is very difficult to get the data out of your SAP systems. So, you have to use SAP HANA. If you're not using the SAP systems, you don't really need SAP HANA. You are free to go for Snowflake. If you have an ERP system and you need to get the data out and move into an SAP or ERP system, and you want to have a data warehouse actually of ERP system, then SAP HANA makes more sense because it can natively talk to SAP. In such a case, you don't want to go for Snowflake. 

    What other advice do I have?

    I would advise looking at your environment. Look at the workload and what you are trying to migrate. There is no one size fits all model. If you are a transaction system and you want to go with Snowflake, I would not advise this solution. If you are a reporting system and you want to migrate, Snowflake is the best choice. 

    You also need to look at what kind of queries people are running. Don't assume that just because you are moving to Snowflake, you are going to cut down the cost by some factor. That is not going to happen. You need to really do a lot of homework and groundwork to know what kind of queries you're running and how can you avoid the compute costs. There is a lot of metadata available in Snowflake. You have to look at all that and then consciously try to improve the numbers. 

    It is definitely a good tool and a good database without any adoption problems. Users who are SQL savvy can immediately adopt this solution. User onboarding is not really a huge exercise. It is a very simple exercise.

    I would rate Snowflake an eight out of ten.

    Disclosure: My company has a business relationship with this vendor other than being a customer: Partner
    PeerSpot user
    MedhaValvekar - PeerSpot reviewer
    Sr Manager at Cognizant
    Real User
    Top 5
    Easy to set up with great cloning and time travel
    Pros and Cons
    • "Time travel is one feature that really helps us out."
    • "The solution could use a little bit more UI."

    What is our primary use case?

    We have day-in and day-out data coming from our various heterogeneous source systems. We read from that and we load data into our target tables, or rather data lake and data warehouse that is built into Snowflake. We can even translate and delete items. Apart from that, we use the tasks and schedule jobs within Snowflake. Once the data is generated into the final data material, we share it with the client for their review.

    What is most valuable?

    Time travel is one feature that really helps us out. If there is some data discrepancy or something wrong that happens with the table, at any point, we can get that data back and time travel via fail-safe features. They're really good. 

    The feasibility to increase horizontal or vertical scaling is great. It really helps a developer at an enterprise level. If you're considering scaling, it won't take much time. 

    We can create cloning via Snowflake. There's a lot of time savings.

    The initial setup is simple. 

    What needs improvement?

    The solution could use a little bit more UI. Something was in process, however, it's not yet deployed or in the version that I'm using it is not deployed. If we have to use any table or any schema in other DB features, the prompt comes over after a dot. Whenever we are using it it would really help if it looked better. 

    If you're running a procedure, it just gives a standard error instead of the exact error captured. If you have to look at it, you need to go into the history to look into which query failed, and we need to figure it out. Instead, if the error, whatever it is, is instead displayed in the history, showing the point of failure, it would be more visible. It would save some time for all the people who are using it.

    There are some reporting analytics that we can use. I'm aware of those. However, if there was more reporting, we'd appreciate that. We'd like for it to become a complete one-stop-shop solution. 

    We'd like to have some automation around small tasks, especially around scheduling.

    For how long have I used the solution?

    I've been working on the solution for two years. 

    What do I think about the stability of the solution?

    In the past three years, I have faced instability. In just one or two instances, I would say when we were running the queries, it was not fetching any result and the error was not proper. That said, that happened in just one or two instances, in the lower environments. Otherwise, the product is very stable.

    What do I think about the scalability of the solution?

    The solution is quite scalable both horizontally and vertically. It's an easy job. We just need to resize it. 

    Within our module, there are around eight to ten people who are working on Snowflake. In a full project, if I'm looking at the holistic picture, there are around 30 to 40 people who are using Snowflake.

    How are customer service and support?

    We've reached out to technical support in the past. In some cases, we were not even able to fetch the data. Or, a couple of times, in the time traveler, the pay phase time was expired and we had to retrieve that data. When that happened, we had to reach out to Snowflake support. In the first instance, they said there was downtime at that server, which we were not informed about. Since it was in the lower environment, it didn't cause an issue. 

    Overall, the technical support was really good. They were on it. They helped as much as they could. For a few things they needed some approvals, and they took that. They got back to us in even less time than was required by the SLA.

    How would you rate customer service and support?

    Positive

    Which solution did I use previously and why did I switch?

    We are also working with Teradata.

    The main difference is that Snowflake is on a cloud server and Teradata is still a legacy system. Teradata was one of our source systems. We were loading it into Snowflake. With Teradata, when you create primary care, something constrains the way you want to do it so that you do not put an additional effort into your ETL. That changes when it comes to Snowflake. If you're clustering something on a case, obviously you end up paying the extra cost. That is one basic and main difference that we saw.

    That said, you can process a huge amount of data in Snowflake. This becomes a challenge in Teradata. When we were reading the data, we had to load that data into Snowflake. When we were trying to read that data, we had to obviously divide it into chunks and then load it into Snowflake. Loading into Snowflake was like a cakewalk. Everything is moving into the cloud now. Legacy systems like Teradata just can't handle the amount of data required. 

    I've worked on many of the legacy systems like Oracle, DB2, et cetera. Migration from one environment to a higher environment was a huge thing. The DVS used to take two or three days sometimes depending on how many tables or what the objects are and what they had to create. Now, with the cloning feature that we have, the idle time for the developers, or even the people who are looking at the data, the analysts, and everyone, is reduced to none. We just clone it, we load the data and the data is available without any hindrances.

    How was the initial setup?

    The solution is straightforward. 

    My Azure ID was created by the DBA. As soon as I had to log in, my user role was set up. To log in to the interface hardly took me more than two or three minutes. Compared to our Data Bricks, it was pretty simple. It's hassle-free. 

    The maintenance of the DBs and the production services are normally taken care of by the team itself who's handling the production support. However, just in case, if there is something, if a huge mishap happens, which we cannot recover, or we would need Snowflake customer support help, that is when the help is taken. Otherwise, the team handles everything in-house. 

    The majority of the cases that we have seen are some queries stuck somewhere and out of the blue. In the case of some source data, it decides to send you a huge amount of data on a particular day. While we have seen some mishaps, a regular case requires our developers to deal with it.

    What about the implementation team?

    We handled the initial setup in-house. 

    What's my experience with pricing, setup cost, and licensing?

    The pricing is fair for all the features that Snowflake is providing. The way Snowflake has emerged in the past few years is impressive. It was just a beginner in the space, and it has become a leader in the market. For all the features it provides at a basic cost, it is impressive.

    There are no extra costs involved unless you need to scale and grow and need more in terms of size. When we started, a medium-size was sufficient. We'd since needed more. 

    The solution allows us to suspend our warehouse as well if we would like. 

    That said, even if you're paying a little more cost for the data safety that you have, you will ensure that there is no data loss that will happen. It's very impressive.

    What other advice do I have?

    My past company was a Snowflake customer. This current company is not, however, it may be on the verge of it. 

    I'm using the latest version of the solution. We switched clouds at some point. I was using it on AWS, and now it is on Azure. 

    I'd recommend the solution to others. I would rate it nine out of ten. 

    Which deployment model are you using for this solution?

    Public Cloud

    If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

    Microsoft Azure
    Disclosure: I am a real user, and this review is based on my own experience and opinions.
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    PeerSpot user
    Buyer's Guide
    Snowflake
    November 2022
    Learn what your peers think about Snowflake. Get advice and tips from experienced pros sharing their opinions. Updated: November 2022.
    656,862 professionals have used our research since 2012.
    director of business operations at a logistics company with 51-200 employees
    Real User
    Top 20
    The query and load speed is phenomenal
    Pros and Cons
    • "It requires no maintenance on our part. They handle all that. The speed is phenomenal. The pricing isn't really anything more than what you would be paying for a SQL server license or another tool to execute the same thing. We have zero maintenance on our side to do anything and the speed at which it performs queries and loads the data is amazing. It handles unstructured data extremely well, too. So, if the data is in a JSON array or an XML, it handles that super well."
    • "An additional feature I'd like to see is called materialized views, which can speed up some run times. I'd like it to be able to be used where you can have multiple tables inside them; materialized view. That would be nice. As well as being able to run cursors, to be able to do some bulk updates and some more advanced querying, table building on the fly."

    What is our primary use case?

    We use it as a traditional data warehousing application that we then set all of our reporting tools on top of.

    How has it helped my organization?

    We are able to consolidate multiple databases into one unified table for more complete reporting. That wasn't possible in our legacy tool that we were using because the query time was just too long. Now we're able to create this unified view of our entire organization and refresh it every 15 minutes; using the power of Snowflake's query is pretty much our biggest use case there.

    What is most valuable?

    The query speed, and the way that it actually executes its queries is the most valuable aspect of the solution. We had some queries that would take hours upon hours to run, and the Snowflake returns the results in about 15 minutes.

    It requires no maintenance on our part. They handle all that. The speed is phenomenal. The pricing isn't really anything more than what you would be paying for a SQL server license or another tool to execute the same thing. We have zero maintenance on our side to do anything and the speed at which it performs queries and loads the data is amazing. It handles unstructured data extremely well, too. So, if the data is in a JSON array or an XML, it handles that super well.

    What needs improvement?

    One area for improvement would be the stored procedures. Currently, their stored procedures can only be executed at a transactional level versus being able to run and do updates and run things in a sequence.

    An additional feature I'd like to see is called materialized views, which can speed up some run times. I'd like it to be able to be used where you can have multiple tables inside them; materialized view. That would be nice. As well as being able to run cursors, to be able to do some bulk updates and some more advanced querying, table building on the fly.

    For how long have I used the solution?

    I've been using Snowflake for about four years now.

    What do I think about the stability of the solution?

    The stability has been phenomenal up until lately. We haven't had any issues until the last month. For the four years prior it was always on; we didn't have any outages. All in all the stability is great. The availability is extremely high. There's just been something in the last month that has caused outages for some periods of hours.

    What do I think about the scalability of the solution?

    It's definitely scalable. We're on a very small usage compared to some of the other clients I know Snowflake has, so it's definitely scalable because we have tons of room to grow for our use.

    Including myself, we currently have five users and they're data analysts.

    How are customer service and support?

    I've only used their customer service in one or two instances, and they were very supportive and helpful. The tool is so user-friendly and straightforward that I've never really had to engage their professional services.

    Which solution did I use previously and why did I switch?

    We didn't really have a traditional data warehouse application. We were just using Microsoft SQL Server, but we didn't actually have a traditional MPP-based data warehouse solution. We were still a very growing organization. As we continue to grow our business and increase in size, we have to get better tools that are meant to actually do what we're trying to do with other tools.

    How was the initial setup?

    The initial setup was pretty straightforward. The permissioning is a little more complicated than it needs to be. It would be nice if it just assumed permissions when you create new tables or new users, but you do have to go and actually permission to everything for individuals and people rather than when you create something. It's just because there's no default role that applies to new stuff created so it's a little more complicated than it should be.

    Our deployment took about one month. I'm the only one involved in the maintenance of the solution now.

    What about the implementation team?

    We hired an ETL specialist to come in and get us set up, but he really didn't understand our business and what we were trying to accomplish. So everything he did, we pretty much paid for and then redid ourselves. But it was pretty straightforward using tools that are built for ETL processes. Understanding the SnowSQL command line tool to a certain degree also helps.

    What was our ROI?

    We don't really have it commercialized or revenue-generating in any way, but what we've seen with it is we've been able to remove all of our reporting and other data needs off of production application. So we're not putting extra stress on things that we need to always have up and running in order to operate the business. That's really our security. It's more of a favorite blanket if you will, is where we're seeing the benefits.

    What's my experience with pricing, setup cost, and licensing?

    For our licensing, we renew every January by $25,000 in both credits.

    Their pricing structure is a pay-per-second usage in terms of credits, but you can get discounts if you buy them in bulk. I think it's $1.10 an hour in terms of usage. We just buy upfront and that gets us taken care of for the whole year.

    Which other solutions did I evaluate?

    We did. I evaluated Google BigQuery and Amazon Redshift.

    In terms of distinguishing features between each of them, it was really just two things. One was the speed factor of query times. The other thing that really sold us on Snowflake was their ability for data sharing. They have a unique product as part of their solution that you can share information directly with other individuals, either in their own additional private cloud or if they're not Snowflake customers, simply sharing a URL link to where they can receive data themselves.

    What other advice do I have?

    It's good to use every day. It's the backbone of our entire reporting platform for both internal and external deployments of reports and visibility. We plan on continuing to grow our usage with it, as we put more and more people into our reporting platforms and bring our customers into more self-service that's going to increase the usage of the tool by the way that it actually serves up the information to the BI platform.

    It's not at this time a transactional sort of database solution. It's truly only meant for data warehousing or data laking, and there's a lot of different ways to do role-level security. So you've got to have a good plan on that, but if you're looking for it to be the backbone of a transactional application, it's not the right tool for that.

    I would rate this solution a ten out of ten.

    Which deployment model are you using for this solution?

    Private Cloud
    Disclosure: I am a real user, and this review is based on my own experience and opinions.
    PeerSpot user
    Solution Architect at a wholesaler/distributor with 10,001+ employees
    Real User
    Stable and scalable, enables us to share the data, and addresses the challenges of traditional data warehouses
    Pros and Cons
    • "The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities. There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business."
    • "They need to incorporate some basic OLAP capabilities in the backend or at the database level. Currently, it is purely a database. They call it purely a data warehouse for the cloud. Currently, just like any database, we have to calculate all the KPIs in the front-end tools. The same KPIs again need to be calculated in Snowflake. It would be very helpful if they can include some OLAP features. This will bring efficiency because we will be able to create the KPIs within Snowflake itself and then publish them to multiple front-end tools. We won't have to recreate the same in each project. There should be the ability to automate raised queries, which is currently not possible. There should also be something for Exception Aggregation and things like that."

    What is our primary use case?

    We are completely migrating to Snowflake, and we are in transition. It is primarily to combine all our data repositories into a single place. We have SAP BW and SAP HANA, and some of our business units have their own databases. We chose Snowflake to consolidate all of our data into a single place and then build enterprise data. We are then going to provide the data for our businesses in shared databases, on which they would do reporting. They will also have the ability to bring in their own data, which is currently not possible. They will also be able to do advanced analytics, machine learning, and AI in Snowflake, which is not fully possible on our current platforms. It will be used for all the operational reporting, such as sales, supply chain, appraising, and merchandising. We just started to do reporting related to sales and supply chain inventory.

    We have its latest version. It is currently deployed on Amazon AWS, but we are moving to Google.

    How has it helped my organization?

    There are so many features that Snowflake offers to address the challenges that people have been facing in the traditional data warehouses for a long time. It allows us to have a single repository for all the data. Currently, we have data repositories all over the place, and we want to bring everyone onto one platform so that it can be utilized across the organization. Currently, we need database administrators and SAP administrators to manage multiple databases and platforms. With Snowflake, we don't need any admin, and there is zero maintenance. All we need is a platform architect who can just manage the Snowflake platform to create databases and security roles, and then you can share the data. By integrating everything into a single Snowflake platform, we have lowered the total cost of ownership quite a bit.

    What is most valuable?

    The ability to share the data and the ability to scale up and down easily are the most valuable features. The concept of data sharing and data plumbing made it very easy to provide and share data. The ability to refresh your Dev or QA just by doing a clone is also valuable. It has the dynamic scale up and scale down feature. 

    Development and deployment are much easier as compared to other platforms where you have to go through a lot of stuff. With a tool like DBT, you can do modeling and transformation within a single tool and deploy to Snowflake. It provides continuous deployment and continuous integration abilities.

    There is a separation of storage and compute, so you only get charged for your usage. You only pay for what you use. When we share the data downstream with business partners, we can specifically create compute for them, and we can charge back the business.

    What needs improvement?

    They need to incorporate some basic OLAP capabilities in the backend or at the database level. Currently, it is purely a database. They call it purely a data warehouse for the cloud. Currently, just like any database, we have to calculate all the KPIs in the front-end tools. The same KPIs again need to be calculated in Snowflake. It would be very helpful if they can include some OLAP features. This will bring efficiency because we will be able to create the KPIs within Snowflake itself and then publish them to multiple front-end tools. We won't have to recreate the same in each project. 

    There should be the ability to automate raised queries, which is currently not possible. There should also be something for Exception Aggregation and things like that.

    For how long have I used the solution?

    I have been using this solution for two years.

    What do I think about the stability of the solution?

    It is all cloud. It is really stable. We haven't seen any problems.

    What do I think about the scalability of the solution?

    We can scale up or down based on our needs. We don't have tons and tons of data, but based on the quality feedback from our vendors, it can handle large volumes and has the competency. With the dynamic scale-up feature, we are confident that it is going to meet all our requirements.

    Currently, our number of users is very limited because we have just started the migration. We don't have many users on the platform. All of our focus is on Snowflake because we're moving to Snowflake, and its usage will increase in the future.

    How are customer service and technical support?

    I do not directly interact with the support, but I believe our platform architect reached out, and he got a response.

    Which solution did I use previously and why did I switch?

    We had SAP BW and SAP HANA as our main data platforms. We are slowly decommissioning SAP BW and SAP HANA and completely migrating to Snowflake. We wanted to have a single repository for all the data. The cost was also a factor.

    How was the initial setup?

    It is straightforward. To expose the data in the cloud, we had to go through our info security and legal, so that's the part that took time. After that is done, the process for setting up the platform, getting signed up with the initial free credits, and signing up the licensing for the credits was straightforward.

    What about the implementation team?

    We are working with a system integrator or vendor for this project. Our strategy is to work with an experienced vendor for the first project, and after that, we would be able to drive things forward.

    Our experience with them is good. They're building the architecture of Snowflake. They have experience, and we have our own thoughts. We are working together and making sure that the architecture is for the long-term and not just for one project. Whenever we see that their focus is limited to the project, we are asking them questions to make sure that they are making the right decision.

    In terms of maintenance, it doesn't require any maintenance, but you do require architects. We have three architects. One architect is responsible for the platform and takes care of creating security rules, grants, and users. We also have an integration architect who is responsible for data acquisition, ETL, and stuff like that. We have a data architect who is responsible for the overall data architecture in terms of what layers we need to establish and how do we model the data and publish that for consumption.

    What's my experience with pricing, setup cost, and licensing?

    There is a separation of storage and compute, so you only pay for what you use. 

    What other advice do I have?

    The key part is skill set because Snowflake is all SQL-driven data warehousing. Internally, we have some SAP BW development resources, and they need to learn and move on to understanding SQL-based coding and custom data warehousing concepts.

    I would rate Snowflake a nine out of ten.

    Which deployment model are you using for this solution?

    Public Cloud

    If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

    Amazon Web Services (AWS)
    Disclosure: I am a real user, and this review is based on my own experience and opinions.
    PeerSpot user
    Anirban Bhattacharya - PeerSpot reviewer
    Vice President at a tech vendor with 10,001+ employees
    Real User
    Top 5Leaderboard
    Exceptionally good technology that addresses data warehousing challenges and is built and designed in a good way
    Pros and Cons
    • "The way it is built and designed is valuable. The way the shared model is built and the way it exploits the power of the cloud is very good. Certain features related to administration and management, akin to Oracle Flashback and all that, are very important for modern-day administration and management. It is also good in terms of managing and improving performance, indexing, and partitioning. It is sort of completely automated. Everything is essentially under the hood, and the engine takes care of it all. As a data warehouse on the cloud, Snowflake stands strong on its ground even though each of the cloud providers has its own data warehouse, such as Redshift for AWS or Synapse for Azure."
    • "There are three things that came to my notice. I am not very sure whether they have already done it. The first one is very specific to the virtual data warehouse. Snowflake might want to offer industry-specific models for the data warehouse. Snowflake is a very strong product with credit. For a typical retail industry, such as the pharma industry, if it can get into the functional space as well, it will be a big shot in their arm. The second thing is related to the migration from other data warehouses to Snowflake. They can make the migration a little bit more seamless and easy. It should be compatible, well-structured, and well-governed. Many enterprises have huge impetus and urgency to move to Snowflake from their existing data warehouse, so, naturally, this is an area that is critical. The third thing is related to the capability of dealing with relational and dimensional structures. It is not that friendly with relational structures. Snowflake is more friendly with the dimensional structure or the data masks, which is characteristic of a Kimball model. It is very difficult to be savvy and friendly with both structures because these structures are different and address different kinds of needs. One is manipulation-heavy, and the other one is read-heavy or analysis-heavy. One is for heavy or frequent changes and amendments, and the other one is for frequent reads. One is flat, and the other one is distributed. There are fundamental differences between these two structures. If I were to consider Snowflake as a silver bullet, it should be equally savvy on both ends, which I don't think is the case. Maybe the product has grown and scaled up from where it was."

    What is our primary use case?

    It is used in my company as well as in my client's company. We are a system integrator, so naturally, we need to have the centers of excellence and competencies in Snowflake.

    What is most valuable?

    The way it is built and designed is valuable. The way the shared model is built and the way it exploits the power of the cloud is very good. Certain features related to administration and management, akin to Oracle Flashback and all that, are very important for modern-day administration and management.

    It is also good in terms of managing and improving performance, indexing, and partitioning. It is sort of completely automated. Everything is essentially under the hood, and the engine takes care of it all. As a data warehouse on the cloud, Snowflake stands strong on its ground even though each of the cloud providers has its own data warehouse, such as Redshift for AWS or Synapse for Azure.

    What needs improvement?

    There are three things that came to my notice. I am not very sure whether they have already done it. The first one is very specific to the virtual data warehouse. Snowflake might want to offer industry-specific models for the data warehouse. Snowflake is a very strong product with credit. For a typical retail industry, such as the pharma industry, if it can get into the functional space as well, it will be a big shot in their arm.

    The second thing is related to the migration from other data warehouses to Snowflake. They can make the migration a little bit more seamless and easy. It should be compatible, well-structured, and well-governed. Many enterprises have huge impetus and urgency to move to Snowflake from their existing data warehouse, so, naturally, this is an area that is critical.

    The third thing is related to the capability of dealing with relational and dimensional structures. It is not that friendly with relational structures. Snowflake is more friendly with the dimensional structure or the data masks, which is characteristic of a Kimball model. It is very difficult to be savvy and friendly with both structures because these structures are different and address different kinds of needs. One is manipulation-heavy, and the other one is read-heavy or analysis-heavy. One is for heavy or frequent changes and amendments, and the other one is for frequent reads. One is flat, and the other one is distributed. There are fundamental differences between these two structures. If I were to consider Snowflake as a silver bullet, it should be equally savvy on both ends, which I don't think is the case. Maybe the product has grown and scaled up from where it was.

    For how long have I used the solution?

    I have been using this solution for close to three years. I kept a tab on Snowflake and its progress since it came into the market.

    Which solution did I use previously and why did I switch?

    Personally, I have worked extensively with Oracle, SQL Server, and Teradata. SQL Server has the Fast Track Data Warehouse (FTDW) appliance. Oracle has both the database and the appliance. I haven't worked on Parallel Data Warehouse, which is a big one offered by Oracle. Teradata is an appliance in itself. There is also Metadata. I haven't worked on DB2. 

    All of these had their own lacunae. Data warehouses had their own problems. There were failures, challenges, and difficulties in adoption, and all of these have been addressed by Snowflake a big way. It has tried to marry the best of both worlds in terms of turnaround time, scalability, adoption, and seamlessness.

    I hail from a classical data warehouse background. Snowflake has been kind of a silver bullet. It is trying to meet the best of both worlds. I wish I could do much more on Snowflake, but I'm tied up with many other things, which is why I'm not able to concentrate that much, but it is an exceptionally good technology.

    How was the initial setup?

    Its initial setup is very simple, which is its plus point. It is not at all a problem. You only need to understand a bit of the cloud ecosystem. When Snowflake is on Azure or AWS, you need to understand

    • What exactly is happening?
    • How these two are handshaking with each other?
    • What part Snowflake is playing?
    • How Azure or AWS is complementing it?

    If these things are clear, the rest shouldn't be a problem.

    What other advice do I have?

    This could be something that might be debated upon, but Snowflake has two parts to it. One is the data warehouse itself, and the other one is the cloud. It is important to know about the cloud in terms of:

    • How a cloud functions?
    • How a cloud orchestrates through its services, domains, invocation of services, and other things?
    • How a cloud is laid out?

    For example, let's take AWS. If AWS is invoking Lambda or something else, how will S3 come into the picture? Is there a role of DynamoDB? If you're using DynamoDB, how would you use it in the Snowflake landscape? So, cloud nuances are involved when we speak of Snowflake, and there is no doubt about that, but a more important area on which Snowflake consultants need to focus on is the core data warehousing and BI principles. This is where I feel the genesis of Snowflake has happened. It is the data warehouse on the cloud, and it addresses the challenges that on-prem databases had in the past, such as scalability, turnaround times, reusability, adoption, and cost, but the genesis, principles, and tenets of data warehousing are still sacrosanct and hold good. Therefore, you need the knowledge or background of what a data warehouse is expected to be, be it any school of thought such as Inmon school, a Kimball school, or a mix. You should know:

    • Data warehouse as a discipline.
    • The reason why it was born.
    • The expectations out of it in the past.
    • The current expectations.
    • What being on the cloud would solve?

    These things on the data warehouse side need to be crystal clear. The cloud part is important, but it is of lesser essence than the data warehouse part. That's what I see, personally, and I guess that's the way the Snowflake founders have built the product.

    As a data warehouse, I would rate Snowflake an eight out of ten.

    Disclosure: My company has a business relationship with this vendor other than being a customer: reseller
    PeerSpot user
    Senior Consultant at a computer software company with 10,001+ employees
    Real User
    Reasonably priced, simple to set up, and expands well
    Pros and Cons
    • "The solution is stable."
    • "I don't know about GCP, if they have connected for GCP. If they don't, they should allow for it."

    What is our primary use case?

    Basically, if at all, we wanted to have an interface for data warehouses on the cloud which worked on Azure or AWS. Snowflake, provides a more intuitive, rapid user interface where people can connect and maintain warehouses and share data among the people in the companies easily. Its pricing model and the model have made maintaining virtual warehouses simpler.

    What is most valuable?

    I appreciate the Snowflake marketplace, where you can drop data and allow other people throughout the world to access it. You can go to the Snowflake marketplace and connect to some data. If somebody else publishes, for example, COVID-19 data or weather data, you can sign up for new data sets and bring them into your warehouse, which I found very interesting.

    You can connect to different cloud sources, including Azure and AWS. 

    You can report out, and all the cloud technologies have connected to Snowflake, allowing you to move the data or get the data into Snowflake. 

    The initial setup was pretty simple. 

    It scales really well. 

    The solution is stable. 

    The solution is reasonably priced. 

    What needs improvement?

    I don't know about GCP, if they have connected for GCP. If they don't, they should allow for it.

    Overall, they're doing great. I don't have any specific complaints or improvements that need to happen.

    For how long have I used the solution?

    I've used the solution for a couple of years now. 

    What do I think about the stability of the solution?

    The solution is quite stable since everything is in the cloud, and the data these days has become cheap with storage and everything in the cloud. Through clusters and warehouses, sizes can be increased or decreased based on usage, and they can be turned on and turned off. Sustainability-wise, I think it's a pretty good solution.

    What do I think about the scalability of the solution?

    It is scalable. The warehouses or auto-scaling features in the warehouses are great. You can go from small to medium to large all the way up to extra large, and there are different auto-scaling tasks that can happen. You can turn it on and turn it off based on the usage or auto-turn it on and turn it off. That's a pretty nice feature to have and we find it both sustainable and scalable for sure.

    I work for clients, so last time when I worked for a client, there was a group of 100 people who were actually signed up to use Snowflake. 

    How are customer service and support?

    I've never dealt with technical support. We did have people from Snowflake working with us directly, and we never ran into any issues that needed troubleshooting. The personnel from Snowflake, of course, would resolve whatever came up. 

    Which solution did I use previously and why did I switch?

    I come from an Azure background as well, so Microsoft also comes with Azure Synapse, where it's a similar functionality as Snowflake, where it's warehousing on the cloud. Azure Synapse is also good. I'm unaware of AWS or GCP, and I heard that Google Cloud Platform also has Big Query and big data capabilities, which are tough competitors for Snowflake and other cloud warehousing tools.

    How was the initial setup?

    The implementation process was pretty straightforward. I didn't set it up, though. I used an already set up version. I just had to connect. I had to push data from Azure to Snowflake, create tables there, and have data loaded into those tables, and that's it. I wasn't doing anything else, so I didn't work on the infrastructure of Snowflake.

    You would need a group of two or three people to maintain the product.

    What about the implementation team?

    I work for a consulting firm, so I don't work for the client, so I really don't know what the company used for deployment.

    What's my experience with pricing, setup cost, and licensing?

    Licensing was based on the warehouse. I don't recall it being very expensive. 

    What other advice do I have?

    I'm a consultant and end-user.

    I'm not currently using the solution right now and do not recall the last version I was on. 

    Now, I'm working for a different client on a different platform altogether. My company, as such, doesn't use Snowflake since we are in consulting. We have expertise in something, and then we help the clients deliver that solution on the technology.

    Potential new users should just definitely give it a shot. They should start off with a POC, proof of concept, for the data that they have, and then, if everything works well and they can migrate in a cost-effective way. 

    I would recommend Snowflake to start off with since it's just picking up over the last couple of years. If I have to recommend anything, however, it would be more Microsoft tools I would recommend since that all comes as a package. You can do Synapse and Azure Data Factory, which is  for ETL. You can also do Azure Data Lake Storage. There are different things that you can do when you buy something in a package like that. That said, I definitely recommend Snowflake if someone wants to give it a shot.

    I'd rate the solution eight out of ten. 

    Which deployment model are you using for this solution?

    Public Cloud

    If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

    Microsoft Azure
    Disclosure: I am a real user, and this review is based on my own experience and opinions.
    Flag as inappropriate
    PeerSpot user
    Mauricio Ruiz Falcón - PeerSpot reviewer
    Senior Information Management Architect at Raken
    Real User
    Top 20
    I like how quickly the solution can be implemented
    Pros and Cons
    • "The features that I have found most valuable are the ease of use, the rapidness, how quickly the solution can be implemented, and of course that it's been very easy to move from the on-premise world to the Cloud world because Snowflake is based on SQL also."
    • "It would benefit from an administration that allows you to be aware of your credit consumption once you have the service so that you may be sure how many credits you are consuming when you use the platform and to make sure that you are making the most efficient use of these resources. In other words, to improve their interface so that you may monitor the consumption of your credits on Cloud."

    What is our primary use case?

    We are a consulting company so our primary use depends on the niche that we are providing the services to and on which of the different versions they have. I think we are mainly using Snowflake Enterprise.

    In general, it is being used for integrating information. Snowflake is a database platform, it gives information to support analytic needs, such as advanced data analytics like machine learning. In some of those cases it is also used for descriptive analytics, for instance BI.

    How has it helped my organization?

    One of example of how Snowflake has improved a client's organization is the democratization, it makes information available to more of the users.

    What is most valuable?

    The features that I have found most valuable are the ease of use, the rapidness, how quickly the solution can be implemented, and of course that it's been very easy to move from the on-premise world to the Cloud world because Snowflake is based on SQL also.

    What needs improvement?

    I think that the area of improvement with Snowflake is to improve the administration. It would benefit from an administration that allows you to be aware of your credit consumption once you have the service so that you may be sure how many credits you are consuming when you use the platform and to make sure that you are making the most efficient use of these resources. In other words, to improve their interface so that you may monitor the consumption of your credits on Cloud.

    I also heard from a company we work for that it could be more user-friendly because it provides some tools but they are not user-friendly.

    Additionally, it would be very helpful if Snowflake integrated machine learning and some other advanced analytics features within their language or product capabilities. Right now, they do it through some other company where you have to buy these capabilities from other vendors. There are some customers that don't have complex needs for machine learning or advanced analytics so they don't have to buy it from another vendor but can use it from the product itself if they have it.

    For how long have I used the solution?

    The whole company has been using Snowflake for about three years.

    What do I think about the stability of the solution?

    In terms of stability, so far it is very stable.

    What do I think about the scalability of the solution?

    Snowflake is very scalable. Our client companies where we implement Snowflake are medium to large sized. These companies have offices in different parts of the world, not just some regions, but companies with office users in different parts of the world. We are dealing with international companies. Their tendency is to increase the use of the Snowflake platform. It would serve all the analytical needs in these companies.

    How are customer service and technical support?

    I have not directly experienced the technical support. It's not part of my job to be involved on those kind of issues, but we constantly receive information as a partner from them and we are very in good touch with them and with the people we are working with, meaning the representatives that are within the Latin American market, which is where I work. They are very open and very fast with communication.

    How was the initial setup?

    The initial setup is easy. Full deployment takes a few weeks. The initial deployment for the first initiatives might take weeks. It's not complex, really. You may have it loaded after a full day and already providing results or interacting, but there are some other companies that have to be implemented to extract and consume the information from the database. But it's very easy.

    Which other solutions did I evaluate?

    There have been a couple of other solutions that we've been participating in the evaluation process of and some others that have been included in the decision process, including Redshift from AWS and also Azure Synapse from Microsoft.

    For instance, AWS Redshift looked like it was easier to implement and to be adopted by the technical users, the programmers and database programmers. So far it has been far easier to adapt this technology. I'm not saying that AWS is a better technology. It's very complex, but at least what I've seen is that for them, it looks like it's been easier to use the first time.

    We liked that Snowflake is able to be used as a multi-Cloud service - it can be used in AWS Cloud, Azure Cloud, or Google Cloud. Whereas AWS, or even Synapse, can only be used in their corresponding networks.

    What other advice do I have?

    I would definitely recommend Snowflake.

    On a scale of one to ten, I would give Snowflake an eight.

    I give it an eight out of 10 due to its room for improvement in the user interface for the monitoring of the credit consumption and that the user experience is not friendly. And also because the machine learning is lacking some advanced analytic features.

    Which deployment model are you using for this solution?

    Private Cloud
    Disclosure: My company has a business relationship with this vendor other than being a customer: partner
    PeerSpot user
    Data Architect at a tech services company with 201-500 employees
    Real User
    Top 10
    Easy to migrate to, easy to use, and easy to set up
    Pros and Cons
    • "It was relatively easy to use, and it was easy for people to convert to it."
    • "The aspect of it that was more complicated was stored procedures. It does not support SQL language-based stored procedures. You have to write in JavaScript. If they supported SQL language and stored procedures, it would make migration from on-prem much simpler. In most cases, if an on-prem solution has stored procedures, they're usually written in SQL. They're not written as what most on-prem DBMS would refer to as an external stored procedure, which is what these feel like to most people because they're written in a language outside of SQL."

    What is our primary use case?

    I have been working on Redshift, Snowflake, and AWS RDS Oracle. In the particular case of RDS Oracle, they were migrating from on-prem Solaris equipment to cloud-based RDS.

    I would suggest Snowflake for anyone with the need for a reporting/business analytics view of their data that wants only wishes to maintain technical FTE's around processing the data into or out of a data repository but, doesn't want to go to extent of technical management of "AWS clusters" for the data repository.

    What is most valuable?

    It was relatively easy to use, and it was easy for people to convert to it. Moved 168 tables and appropriate indices to Snowflake with minimum modification to Current Oracle DDL. The largest degree of change was setting up the corresponding access Hierarchy to duplicate what was in Oracle ( customer had separate permission structures for application vs Admin/support vs direct reporting access to the data).

    What needs improvement?

    The aspect of it that was more complicated was stored procedures. It does not support SQL language-based stored procedures. You have to write in JavaScript. If they supported SQL language and stored procedures, it would make migration from on-prem much simpler. In most cases, if an on-prem solution has stored procedures, they're usually written in SQL. They're not written as what most on-prem DBMS would refer to as an external stored procedure, which is what these feel like to most people because they're written in a language outside of SQL.

    The other thing that people found difficult to deal with was that they had several Oracle DBAs who were very experienced DBAs, but they were used to on-prem. They were used to having the ability to turn any dial and flip any switch. Moving to Snowflake did cause some issues there because they had to completely readdress the fact that they couldn't touch the engine, and they had to spend more time analyzing performance.

    For how long have I used the solution?

    I probably used it about six months ago. I haven't been working with a client who is currently on this platform.

    How are customer service and support?

    I haven't had to call on them for a problem at that level.

    How was the initial setup?

    It was a cakewalk. The biggest thing that's hard to do with it is that you have to do an analysis of performance over time to determine the scale because they separate compute and storage.

    Scaling the query to a proper size compute is the larger aspect of the problem for most people. That's because you're looking at something completely different. The problem is that you're now trying to figure out what is the largest compute you need to keep performance where you want it without going too large. If you were in an on-prem scenario, you would tweak and twaddle all the dials. You might rewrite the query, but at the end of the day, you're still working inside the same physical acquisition or same physical resources, whereas in Snowflake, you're literally saying that you've got a 10 million row table as part of your query, but what is the necessary compute facility that you need to run queries that are running against that table.

    What's my experience with pricing, setup cost, and licensing?

    It is hard to say because we're usually engaged in the transition as opposed to the long term. Their storage costs are easily within pennies of what AWS S3 would normally cost. 

    Most of the clients I've been working with are in the financial sector, and they're relatively small. I would put them in an SMB connection. The first thing we have to bring up for people is that they're going to build this. They shouldn't store their data in S3. They should pipeline directly into Snowflake and use it on their storage. So, the cost is a big issue because these are small to medium size companies, and that is the biggest thing we had to price point for them.

    What other advice do I have?

    The biggest conversion problem we've seen so far is when someone had a large number of stored procedures that were SQL-based, as opposed to external stored procedures written in C or whatever the DBMS would support. Converting those stored procedures either to a SQL script or to a stored procedure or function that's based on JavaScript is the biggest challenge that most people we've dealt with are having. That's because they have to relearn the language they're writing their logic in.

    I would easily rate it an eight out of 10.

    Which deployment model are you using for this solution?

    Public Cloud

    If public cloud, private cloud, or hybrid cloud, which cloud provider do you use?

    Amazon Web Services (AWS)
    Disclosure: I am a real user, and this review is based on my own experience and opinions.
    PeerSpot user
    Buyer's Guide
    Download our free Snowflake Report and get advice and tips from experienced pros sharing their opinions.
    Updated: November 2022
    Buyer's Guide
    Download our free Snowflake Report and get advice and tips from experienced pros sharing their opinions.