Snowflake Reviews

My company wanted to have all our data in one single place and this what we use Snowflake for. Snowflake also allows us to build connectors to different data sources. The ultimate goal is to provide reporting and analytics to all departments in the company.

This solution could be improved by offering machine learning apps. 

We have used this solution for one year. 

This is a stable solution. 

This is a scalable solution. 

Before Snowflake, we used Azure.

I worked with a Microsoft partner to set up the entire thing. This took three months. 

We have not yet experienced ROI. 

Overall, this is a helpful tool with a friendly interface. 

I would rate this solution an eight out of ten.

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.

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. 

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.

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

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.

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.

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.

Positive

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.

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.

We handled the initial setup in-house. 

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.

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. 

Our current plan and use case for this solution is to migrate the data from on-premises to the cloud. We are currently using on-prem monitor data and providing it on the cloud. We are using Snowflake so that once the data is in there, we are trying to create shares over it so that external systems can't consume it.

The features I found most valuable with this solution are sharing options and built-in time zone conversion.

I see room for improvement when it comes to credit performance. The other thing I'd like to be improved is the warehouse facility. 

In the next release, I'd like to see easier connectivity to the on-premises tools.

I have been using this solution for about three years.

My impression from using this product for the last three years is that it is quite stable.

My impression is that this is a scalable solution. There are around 200 users of this solution at our company, including three administrators.

The initial setup process was not that complex and it took around six months.

The implementation was done by an in-house team.

My impression is that the pricing of this solution is reasonable.

I would rate this solution a seven, on a scale from one to 10, with one being the worst and 10 being the best.

I mostly build or design data warehouse analytics solutions using Snowflake.

The productivity across the teams that use Snowflake I believe is higher than it would be without the solution.

Snowflake has three great features: Snowpiping is proving to be very valuable, Time Travel is excellent, and Snowpipes are another great functionality the solution has made available.

Snowflake needs transparency over costs and pricing.

I have been using the solution for three years.

I give the stability an eight out of ten. We rarely have issues.

I give the scalability an eight out of ten.

I have used many on-premise solutions in the past and also Azure Synapse Analytics.

The initial setup is straightforward. I give the setup an eight out of ten.

A basic implementation is quick and we only have to set up Snowflake and the cloud service. We need one engineer and one designer for the implementation.

Depending on the complexity of the implementation, we may need to use a third party or help from the vendor.

Part of the problem with the pricing is that it is very difficult for businesses to get an idea of how expensive it might be until they actually start using Snowflake. Until they start pushing large amounts of data through, we will not really know. I believe that it is very difficult for businesses to make a commitment.

I give the solution an eight out of ten.

My advice is to start Snowflake and not spend too much time thinking about how we could use the solution or what it could be used for. The key is just getting started.

My current client is migrating from an on-premise data warehouse to the cloud, and they need to consolidate the data lake. I'm using Snowflake to develop the data lake and build data bots for certain functionalities. I've also used Snowflake to aggregate and clean data for my client's analytics.

I like Snowflake's data exchange capabilities. It can exchange data with downstream systems and other vendor partners as well.

There are some challenges with loading unstructured data and integrating some message queues or brokers. In one project, we had a problem connecting to one of the message queues and we had to take a different route altogether on Microsoft Azure. 

I started using this product about two years ago at my last company. Now, I'm a registered Snowflake partner, so working with Snowflake for one of my clients.

My clients haven't faced many stability challenges. It is a relatively new product that's still evolving. They're using it mainly for POCs, so they haven't faced any problems. 

The most valuable aspect of Snowflake is its scalability. The volume of data, which I have seen across almost in terms of five terabytes and other terabytes of data, I didn't see issues.

Snowflake technical support is good. At my previous company, they had a customer success officer for critical accounts, and they were accessible. When I registered as a partner, I also got a quick response from support. I would rate their support eight out of 10.

Positive

Setting up Snowflake isn't complex. I've not seen any challenges.

They have different pricing structures based on data usage. I think they have three or four tiers you can scale through. Most of the clients see an advantage from this type of licensing. That's the reason they go for it. It's priced competitively with other solutions.

I rate Snowflake eight out of 10. 

We're using Snowflake for Power BI Cloud. We had a cloud version of Snowflake, so we were connecting to the Snowflake database and importing required tables into our system, Power BI Desktop. From there, we linked those tables and created a semantic layer, an internal layer between the frontend and backend, and then we tuned the data. Then we used both the tables to tie into the dashboards that we developed. The dashboards show the sales information or marketing information.

It's a cloud solution.

I like the entire database. This is the advanced version of the cloud version, so it's really a flexible tool. If you have it implemented at home, you can access it from anywhere.

Sometimes when I'm trying to refresh the data, my different application or tool has to connect to its backend database through the connection I create. Sometimes, I face some issues like not having permissions. These aren't as crucial, but there are common errors sometimes where the database is down, or a table is nullified and a new table is added and you are not given access to that. With those errors, you don't have permissions.

I have been using Snowflake for a year.

It's stable.

The scalability is good. It handles a lot of data, and the processing speed is very high.

It's straightforward. You have to have a rule, database names, and a schema name.

When somebody deploys it and gives me the URL and the required tables to use, I use the URL and configure it from the frontend side, reporting side that could be more like Power BI or Tableau, and I start using it.

I would rate this solution 8 out of 10.

We're ingesting third-party data analytics into a database held within Snowflake. We have pre-production and production environments with integration to staging and production schemas.

It has improved the way our organization functions. However, we're still pretty elementary in our understanding of how it all works and the complete capabilities of Snowflake.

The adaptation to development languages is most valuable. Our developers can SQL code or something else. It has been convenient in that regard.

The data sharing capabilities across business units within the organization should be better. There could also be better integration.

I have been using Snowflake for a year and three months.

We have high confidence in it.

We have high confidence in its scalability. In terms of its users, for our solution, we only have a team of 10, but we have plans to increase its usage.

We haven't had any technical contact. All of it has been internal for our organization.

This is a net-new solution. So, it's brand new. We chose Snowflake for a variety of reasons, but mainly, we chose it for its scalability and data sharing capabilities.

I would rate it a three out of five in terms of complexity just because we didn't have any Snowflake developers that were available. The implementation took about three months.

We implemented it on our own.

We have not yet seen an ROI.

We're based on credits. So, we're paying four and a half dollars of credit. There are no additional costs. I would rate it a two out of five in terms of pricing.

I would advise ensuring that you have the expertise with domain knowledge in Snowflake. The time from initial concept to deployment could be expedited extremely fast. Just from our internal learnings, we see that our time to production has increased month over month.

I would rate it a six out of ten just because we're unaware or naive to the full capabilities of the product. However, I would highly recommend it in terms of setting up data warehousing internally over an Azure solution, such as Synapse, or something else.

We are silver or gold partners. The main use case is that we are building a data lake. We are creating a couple of downstream applications as well that will be used by data scientists. So, we will have a single data lake that will be used across the organization by different business domain users. The data is multi-source. We have data from SAP, JDE, and some Excel files.

The speed of data loading and being able to quickly create the environment are most valuable. 

For data, it provides built-in security and compliance with different standards, such as SOC 2, ISO, etc. So, we don't have to do a separate audit for compliance.

There are some gray areas. For example, there is no clarity on where the data sits exactly. That is their proprietary information, and they are not sharing those details. 

Its price should be improved. On the cost-side, it is more expensive than others.

If they could bring in some tools for data integration, it would be really great.

I have been using this solution for almost two and a half years.

It is pretty stable. Its stability is excellent.

It is scalable. As of now, there are 500 users, but slowly, we are planning to roll out to multiple regions. It is currently in Europe, and we will be rolling it out to the APAC and USA regions. By the year-end, there will be more than 1,000 users.

They're perfect. They're excellent. It could be because we are partners.

It is straightforward. It is not that complex.

Our own team deploys it for customers, but the initial configuration is done only by the Snowflake team because that is their area. 

I have worked with multiple clouds, and cost-wise, it is a bit costlier than others, such as Redshift. Its price should be reduced.

I would rate it an eight out of 10.