Snowflake Reviews

We use Snowflake for data warehouse modeling and reports.

Once you have finished your designs they can be easily imported to Snowflake and the information can be readily accessed without an IT expert.

The documentation could improve. They should provide architecture information.

There could be better integration with tools other than the common databases used to receive data. There are other tools that have ETL tools within, such as Tableau. You are able to work with information prior to sending it to Tableau. This feature would be nice to have in a tool from Snowflake.

In a future release, they should make it easier to do reporting. A drag and drop type feature would be good. If not a drag and drop feature, there should be some other easier way to do it than it is now.

I have been using Snowflake for approximately six months.

The experience that we have had until now is that we can use the Snowflake very well from the videos on the web. The knowledge that our company already has regarding this solution has helped. We are producing some very sophisticated solutions. There is plenty of material on the web that you would be able to have lessons and learn.

We have worked a lot with Tableau previously.

We deploy the solution on-premises because we are developers, the customer is the one who has it on the Cloud. We helped them with the on-premises deployment and then we install the software and we deployed our solutions made on-premises. We complete any changes that need to be done in order to work in the customer's landscape.

The time of the deployment depends on the solution the customer requires. If it's a small solution, typically it will take approximately two weeks. A medium solution, that takes from two weeks to eight weeks.  However, it depends on what you are trying to accomplish with the solution. If you are trying to do a very complex data warehouse, it's not the tool that times the most time, it's the analysis and design that takes the most time for deployment. Once that you have the analysis, design, and you transport them to Snowflake this is not difficult.

In any BI solution, you have a lot of changes because of what you need to do with the end-users, there are a lot of changes to the end-user. This can also take up some time for the deployment for the first time. It can take two to six weeks for a medium-sized project.

On average a small project can take three people. That's in small BI projects, in some customers that we have the project takes a maximum of six weeks in order to have all the data fields. This is not for a whole data warehouse but for sales and customers. Those are all small to medium-sized projects, that require three people maximum for deployment. You might always want to have in addition, an analyst and the senior architect. 

Most of our team are technicians.

Snowflake has a lot of capabilities and performance. However, the tool is not a silver bullet and can do everything. If you designed what you need according to the tool, then everything is going to be okay.

This is true for any tool. Many people start the projects without validating what they are going to expect to have at the end, they receive a big surprise. They were thinking that the tool has this capability and it doesn't have it or perhaps it has the capability but the design you have does not work correctly.

If you see the percentage of projects in the different customers in many places, such as in Mexico, Florida, and Miami. Snowflake is a tool that is currently being used but has not been in the past. There is not a lot of history.

I rate Snowflake a six out of ten.

We have not used Snowflake long enough to better rate it. If we had a lot more formal education or had more information or reference manuals our experience would be better.

We use the solution for a data warehouse and we generating reports and dashboards.

Snowflake has improved my organization because of its high performance compared to the old way we used to operate with Microsoft SQL Server. We are migrating everything from SQL Server to Snowflake. It used to take a lot of time to query the database but now it is done a lot faster, we receive millions and billions of reports. This is a major benefit because it is our major use case.

The most valuable features are sharing data, Time Travel, Zero Copy Cloning, performance, and speed.

The solution is very easy to run the queries. We have a built-in query optimizer in Snowflake that works very well.

The UI could improve because sometimes in the security query the UI freezes. We then have to close the window and restart.

There should be an IDE concept similar to the Java IDE or Eclipse feature. I should be able to see all of the functions available on a particular object. Every time we need to go to the Snowflake documentation and look if there are any methods we need. It is hard to remember everything, go and search, and use that that eventually found method. If it was possible to list out all the methods and functions available in an object that would help the developer's a lot.

In an upcoming release, we should be able to send or receive data from external systems but this is not able to be done. There should be built-in logging and monitoring features, we should not need to be dependant on third-party solutions, such as Splunk. There should be more DevOps features to reduce the usage of third-party tools. If these features were part of Snowflake it would be a fully functional complete solution.

I have been using Snowflake for approximately two and a half years. 

They claim zero maintenance support and from my experience, I would agree with that statement. When I was on a previous project we had a lot of support for the Netezza platform we were using. We had approximately twelve people, three onsite and seven offshore. When we migrated from Netezza to Snowflake we reduced the number of people required and kept only some of the team as developers. There is very little support required for this solution. Stability is very good in SnowFlake.

The scalability is built into this solution as being on the cloud. It is able to scale in all directions. Additionally, they have a multi-cluster warehouse, and based on the business use case it is very good.

There are approximately 4,000 portals. However, we do not know how many users our clients have that are using their portals.

We are building new data warehouses and we are migrating from SQL Server to Snowflake.

The support is very good. We create tickets and they respond with a solution.

We were using SQL Server previously and we switched because of the increased performance, multi-clustered shared environment, scalability, and we wanted to use a cloud-based solution.

Everything with the installation went smoothly. I believe when I joined the company Snowflake was already here. They bought the Business Edition that is encrypted everywhere because they are a financial insurance company and most of them choose the Business Edition because of the security.

The company I work for used SnowFlake integrators for implementation assistance.

I have evaluated Eclipse and IBM Netezza.

The solution is very easy and flexible to integrate with any type of API.

I rate Snowflake a nine out of ten.

The solution is primarily used as a data warehouse.

The solution is very easy to use.

The product is very stable and flexible. The performance is good.

The product is quite scalable.

The solution needs to offer more functionality related to machine learning and artificial intelligence.

The solution needs more connectors.

I've been using the solution for close to two years.

The solution is very stable and extremely reliable. There are no bugs or glitches. It doesn't crash or freeze. The performance is very good.

The scalability of the solution is very good. If a company needs to expand it, it can do so with ease.

We have about 100 people on the product currently.

Technical support overall has been good. They are helpful and responsive. We have no complaints. 

I have some experience with Teradata.

There is no installation process, as it is run as software as a service on the cloud.

For deployment, I would say two to five people would be enough. It depends on the size of the project and can have from one person to 20 people supporting it. It really depends on the implementation. The people would likely be admins, engineers, and managers.

The product requires the purchase of an annual license.

Before choosing this solution, we looked at SQL Server and Teradata.

We're customers and end-users.

We're using the latest version of the solution. I can't speak to the exact version number.

I'd rate the solution at a nine out of ten. We've been mostly very happy with its capabilities.

I'd recommend the solution to other users and companies.

I use this solution for actively building out the cloud data warehouse and data platform for enterprise level customers as well as startups. Generally, our clients are looking for a data warehouse on the cloud to enable them to scale infinitely at a lower cost. I've worked for a finance analytical team building their data lake, the data platform on top of Snowflake, as well as for a telehealth team. It's basically about getting data from multiple sources and building out an entire data platform with data governance. We are customers of Snowflake. 

One small company I worked with had a MySQL RTS based instance and were using AWS RDS with MySQL on top of that. As a result they were unable to scale their database because there were around half a million queries being run per second as well as data querying and data updating. The migration to Snowflake helped the company because there are no limitations in the cloud and no longer restrictions on the queries. Performance for end users improved whether they were internal or external clients. They used to sell the data through APIs so this migration helped to grow their business overall as well as the ML team efficiency and the productivity of users who previously used the data platform. 

The most valuable feature of Snowflake is the query performance. Snowflake is the most efficient way for real-time dashboards or analytical business intelligence reports to be sent to the customer. There are a couple of areas where they have recently improved. One of the key features they introduced is an internal, table-based merch as well as storing of the unstructured data. You can now build a table out of unstructured data, metadata. This hasn't yet been officially announced.

Although the UI has improved lately, they still need to work on their UiPath, the workspace area.

I've been using this solution for two years. 

It's an infinitely scalable system, but if you use terabytes or petabytes of data, then you need to tune the levels. Each day, we get four to five gigs and overall, our data warehouse has 100 gigs plus, it's huge data. 

Our clients previously used the RTS based MySQL and migrated to Snowflake from there. The primary reasons they moved was because of scalability and performance. Other than that, Snowflake reduces costs quite significantly. I also have experience with BigQuery which is particularly used for Google Cloud although these days they have a multicloud enrollment. Snowflake is vendor independent so you don't have to stick everything in Google Cloud. In terms of performance, Snowflake is faster than BigQuery. 

The advantage of Snowflake is that it's easy to deploy and they take care of the setup. Basically, it's a cloud warehouse and doesn't need to be registered on any website. It's easy. It just requires dedicating space and registering. It shouldn't take more than a couple of days. 

Snowflake is reasonably priced, close to half the cost of some other solutions. 

In terms of performance the solution is good when compared to the analytical workloads and good in comparison to Redshift or BigQuery. The performance is on a slightly higher level, but when it comes to real-time performance, NoSQL is better than Snowflake, but that's in rare cases and depends on the particular requirement. Overall, for the analytical use case, Snowflake is a good solution and in terms of availability, it's a cloud data warehouse, so  they do replication and the like. 

It's important to understand your business needs, because these tools need to be properly modeled and they have their own advantages. If you're new to Snowflake, it's worth starting slowly for one month and move gradually, because if it's a complex system and you move everything to Snowflake without good architecture, then you can get stuck with the original problem. It's worth taking the time to make it efficient and then design modeling; there are SnowPro certifications as well. 

I rate this solution an eight out of 10. 

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.

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.

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.

I have been using this solution for two years.

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

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.

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

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.

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.

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.

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

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.

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.

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.

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.

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.

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.

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.

We're running a POC to test scalability, performance, on-demand resource management, workload management, et cetera. The security aspect will also be important for us.

The product offers a lot of great features.

Architectural-wise, it's got great architecture. That's what we are looking for. It's kind of decoupled from storage and has virtual warehouses. We like that we can travel and keep things virtual. For us, the virtual warehousing is likely the most valuable aspect. You can spin up as many virtual warehouses that you want. That's quite useful as a feature.

I haven't found that the solution is lacking any features. It's quite complete.

I would like to see a client version of the GUI. Right now, it is a web GUI, which has stored the SQL, the worksheets. We are asking for that from Snowflake. We'd like to understand how can we save these worksheets on our local desktop. That is not there at this point.

I've been using the solution for about the past year as part of a POC.

In the past, we've used an SQL server. On the cloud side of it, we do have some experience. Snowflake, however, is the new data warehouse solution that we are looking into it.

If necessary, we may have to get into Synapse, and do a kind of a pilot project with that as well. We may evaluate them both to see which is better. We are not there yet. We are just working on Snowflake.

We are a direct customer and end-user.

We've been using the solution during a POC for the last year or so. It's a pilot project to test its feasibility for our company. We're just starting to get performance stats and stuff like that.

I'm not sure which version of the solution we are currently using. I don't recall the exact version number. Usually, people are running the latest version. Whatever the latest available option is is likely the number we are on.

I'd rate the solution at an eight out of ten. We're still in the POC phase, however, based on what we have seen, we are quite satisfied.

We implement this solution for our customers. It is a cloud data warehouse. It is SaaS, and it can be run on Azure, AWS, or something else. We are using its latest version.

It is a very good platform. It can handle structured and semi-structured data, and it can be used for your data warehouse or data lake. It can load and deal with any data that you have. It can extract data from an on-premises database or a website and make it available in the cloud.

It has very fast implementation and integration as compared to other solutions. There is no need for the DBA to manage or do the day-to-day DBA tasks, which is one of the greatest things about it.

In future releases, it can also support full unstructured data.

We have been using this solution for a year.

It is stable.

It has very good scalability. Your data can grow in the platform. We have at least 50 users of this solution in an organization.

Their vendor is wonderful. I only have good words for them.

It is not too complex. Its implementation is easy even for those people who don't know Snowflake and are coming from other environments, such as Oracle or SQL Server.

It can be implemented very quickly. Our customers in Israel implemented it very quickly. It was much faster to implement than other platforms.

It is on a monthly basis. It is based on your usage. There are no additional costs from the point of the licensing fee.

We do give some kind of evaluation to the customers about how much it is going to be. You can decide in Snowflake the virtual machine that you are using for customers. There are several kinds of virtual machines that you can use. It is similar to the clothing sizes: small to extra large. If you need more power in the coming month, you can decide in advance and take a more powerful machine. You can just select it from the platform. You can also decide which machine you want to take for extracting data.

I would advise others to check themselves how fast its implementation can be and how responsive it is. I would also recommend evaluating it before choosing other solutions, such as Microsoft Synapse or Amazon Redshift. You can test it yourself by using a test case. You can try to load the data on each platform, which can take a few weeks, but you will get to know the advantages of this solution. It is very different from other solutions.

I would rate Snowflake a nine out of ten.

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. 

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. 

I have been using this solution for three years.

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.

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.

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.

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.

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. 

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. 

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.

We primarily use the solution for the data warehouse.

The solution offers everything you'd find on Azure or AWS. It has a lot of industry-standard features and capabilities.

The product has excellent autoscaling. We can actually compute and scale-out at the same time without having to depend on other tools. You can do it on the fly, or within queries, etc.

The Visual Copy Cloning is definitely one feature that everyone looks forward to due to the fact that it gives you regular backups. 

The solution offers a very good time travel function that allows you to travel back in time to before your systems we corrupted. You can go back into your history and grab the last backup before corruption so that you regain almost everything you need. It gives you 90 days to fetch the data back if you need to. It's better than Azure options.

We've spoken with Snowflake about the fact that there are a few bare minimum requirements now these days for any data cloud, data lake, or platform. They've lacked a bit here, however, they're adopting some new measures that will be available in the next release, so that is sorted.

Snowflake is partners with only AWS as a cloud platform. However, in India, Microsoft has got a big subscription. The product needs to be able to adapt to Azure a bit more in order to meet the local market demands. 

It's difficult to know how to size everything correctly.

They should incorporate at least a basic ETL framework.

It's early days, however, I would put the solution at a seven out of ten. It needs a bit more time to mature. If I were to look at it strictly from a warehousing perspective, I'd rate it at an eight out of ten.

I've been using the solution for about ten months. I started using it originally when we started our partnership with the organization.

The one thing that seems to be unclear for Snowflake customers is the cluster sizing. No one seems ot know how to compute that.

For example, if I'm running a warehouse that is extra small, as per my query performance, if I see like if this query will run perfectly on the machine I will have. However, I don't know which machine to go for. There's no direct comparison between an extra small, or a small, or a medium warehouse. I never get to know, unless I run the case query on different sizes, which to go for. It's hard to say "Buy only this and go for that particular size". Sizing seems to be a bit of trial and error. If they had some sort of benchmarking around their cluster size, that would be helpful.

The initial setup is pretty straightforward. We didn't have any issues with implementation. It's not too complex.

The pricing of the solution is fine. The storage is pretty cheap. They also offer a lot of discounts. The cost shouldn't really be a problem. 

That said, the agreement should be more of a subscription basis instead of asking for a commitment. For example, Microsoft tells your the price and allows you to subscribe to that, whereas, Snowflake wants you to commit to a certain amount of time before they really give you firm pricing. 

We're partners with Snowflake. We've been partners for just under a year at this point.

I'd definitely recommend the product. It's worked quite well for us. 

A new customer needs to understand, however, that they need a roadmap of at least five years when they are deciding on their data warehouse. They should compare costs and sizing to make sure they are getting the solution that makes sense for their current and future needs. 

The solution integrates well with other applications, and if you need it to integrate with existing applications, you still should check to make sure it's possible.

I wouldn't necessarily recommend Azure over Snowflake, as they aren't really a good comparison. Snowflake is more focused on data repositories and data warehouses. AWS does give you many options, however.