Snowflake Reviews

I am using Snowflake for all our apps and data warehousing requirements.

The most valuable feature of Snowflake is it's an all-in-one data warehousing solution. 

Snowflake could improve migration. It should be made easier. It would be beneficial if it could offer some OLTP features. One of our customers was using Oracle for both data warehousing and OLTP workloads, and they were able to migrate their data warehousing workloads to Snowflake without major issues. However, for some of their OLTP requirements, such as needing a response time of fewer than 10 milliseconds for certain queries, Snowflake is currently unable to provide that.

It would be beneficial to see more integration and reporting tools embedded within the platform, similar to what Microsoft offers with its data warehouse and database solutions. Oracle, on the other hand, does not have such features. While Snowflake has a lot of options available on its marketplace, it would be helpful if it could provide more optimal options for users who are migrating from other environments. It would be great if they could follow the same path as Microsoft in this regard.

I have been using Snowflake for approximately one year.

Snowflake is stable.

We have two clients using this solution.

The solution is highly scalable.

We don't have direct support for Snowflake as we support our clients. If any support is required, our clients connect with Snowflake's support team and get the necessary assistance. They own the support account.

The initial setup of Snowflake is easy. We only need to create a login, there is no conventional setup.

When it comes to migrating from a previous platform to Snowflake, it largely depends on the size of the data warehouse, the number of integrations, the existing data pipelines, and the type of data sources. The complexity and size of the current deployment will determine how difficult the migration process will be.

The ROI appears good on paper, particularly in terms of cost reduction in operations. However, as companies have only been using Snowflake for a year and it's hard to say for sure. It looks promising for now, but it will take a year or so to see if it holds up in practice.

Snowflake is a cloud-based solution that uses a pay-as-you-go model. The storage and processing are separated, and you are mainly charged for the processing power you use. Additionally, there is a charge for storage, but the primary cost comes from the processing. You can choose different sizes of processing units, also known as warehouses, for your specific workload or requirements. You pay for the per-second utilization of those computing resources.

Snowflake is cost-effective. However, the cost can depend on how it's being used and how efficiently the code is written. If engineers don't write efficient code and usage is billed based on processing, it can become costly. If they write optimal code and choose the best solution, it can reduce costs in comparison to other options, such as Oracle.

I would recommend this solution to others.

I rate Snowflake an eight 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.

We primarily use the solution to build some cost-effective solutions for a data warehouse, mostly for all non-transactional data.

The solution is very fast. It's not clunky or slow.

The product, overall, is quite inexpensive. It's very cheap to use.

The solution is extremely user-friendly and easy to navigate. The user experience is very good.

The initial setup is pretty straightforward. It's simple.

We found that the initial setup was pretty easy.

The solution has been stable and has provided good overall performance.

A company can easily scale the solution. It's not too difficult to pull off.

The technical support on offer is excellent. They're helpful for the most part.

There are always a few operation updates here and there that can be made. However, overall, there aren't any features or glaring shortcomings. It's pretty good. We can't complain.

While the solution is quite inexpensive, there is always a push from clients that want it to be cheaper in the future.

I have about six years' worth of experience with the product. I've been using it for a while. I'm comfortable with its aspects. I've used it over the last 12 months as well.

The stability is very good. There are no bugs or glitches. It doesn't crash or freeze. It's reliable. The performance is good.

The product scales quite well. If a company needs to expand it, it can do so without any problem.

We deal mostly with clients that have medium to large-scale organizations. It works well for both.

Technical support has been excellent. I'd rate them nine out of ten. They are knowledgeable and responsive. We are quite happy with the level of assistance we receive if we need help.

We've used a few other solutions including MySQL and a few other notable databases.

Right now, we are looking for some other options as well.

The initial setup is quite simple. It's a straightforward process. It's not overly complex. A company shouldn't have any issues with the implementation process.

We are implementors. We can implement the solution for clients if they need us to.

The product is very reasonably priced. It's quite cheap to use. It's less expensive than, for example, Oracle.

We are implementors of the solution.

We are using previous versions of the solution. It may not necessarily be the latest version all the time.

I'd advise other organizations to try it out and play with it a bit to see if it would fit their needs.

Overall, I would rate the solution at a nine out of ten. We've been mostly very happy with it.

I am a solutions architect for Snowflake.

The Time Travel feature is helpful for accessing historical data and the ability to clone external tables is useful.

I would like to see more transparency in data processing, ATLs, and compute areas - which should give more comfort to the end-users. 

Improvement to the end-to-end process of loading data into Snowflake could be made as well.

The product is stable so far.

The product is scalable enough.

The initial setup is not complex.

I believe that pricing is reasonable for this solution.

Snowflake is easy for business users to implement, allowing them to start small and grow big.

I think people are still debating on whether they should still continue with S3 and add Snowflake or, whether they should take away S3 and completely rely on Snowflake.

I would rate this solution an eight out of ten.

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.

I have used it in my previous company. It was just a SQL server data warehouse using reporting tools on top of it. It was an on-premise SQL server environment, and it was a typical data warehouse use case, but we wanted to do things faster and more cost-effectively. 

We used it to modernize our data warehouse. We didn't want to invest more in on-premise servers, and we were looking for a way to quickly get more data joined together. 

It had definitely improved the way our organization functioned at the time.

The overall ecosystem was easy to manage. Given that we weren't a very highly technical group, it was preferable to other things we looked at because it could do all of the cloud tunings. It can tune your data warehouse to an appropriate size for controlled billing, resume and sleep functions, and all such things. It was much more simple than doing native Azure or AWS development. 

It was stable, and their support was also perfect. It was also very easy to deploy. It was one of those rare times where they did exactly what they said they could do.

Their strategy is just to leverage what you've got and put Snowflake in the middle. It does work well with other tools. You have to buy a separate reporting tool and a separate data loading tool, whereas, in some platforms, these tools are baked in. In the long-term, they'll need to add more direct partnerships to the ecosystem so that it's not like adding on tools around Snowflake to make it work. They can also consider including Snowflake native reporting tools versus partnering with other reporting tools. It would kind of change where they sit in the market.

I have been using this solution for about three years.

We didn't run into anything. We had outages for a couple of seconds, but they were related to Amazon or AWS. They weren't related to Snowflake.

We scaled it a little bit. We didn't have a lot of data to scale, as a lot of companies do. We only had a couple of terabytes of data, which is insignificant for a cloud platform. 

The development team had three or four people getting data in. Then report people were also using the platform, but they didn't really have to know that it was Snowflake because they were going at it through a reporting tool. There were probably 30 or 40 people writing queries against our reporting tools, which were, in turn, using Snowflake.

They were really good. They were very responsive. There were never any issues with them. I would give them a ten out of ten.

I've used a lot of different data warehousing solutions at different companies.

It was easy as pie. In a couple of hours, it was up and running, and we were loading the data in. We had a fairly senior developer for that. He knew SQL server and queries very well. If you're used to developing in any type of SQL environment, you can jump in and use Snowflake really quickly.

It is per credit. It has a use-it-as-you-go model. We bought a chunk of 20,000 credits, and they were lasting us for at least a year. We didn't have the scale of data like a much larger company to consume more credits. For us, it was very inexpensive.

Their strategy is just to leverage what you've got and put Snowflake in the middle. It doesn't make it expensive because most of the organizations already have reporting tools. Now, if you were starting from scratch, it might be cheaper to go a different way.

If time to value is your primary goal, then I would recommend going for Snowflake over one of the other cloud providers.

I would rate Snowflake a ten out of ten. It is one of the few products in which everything demos well. It actually did everything they showed in the demos. We really couldn't find any gotchas in it. It kind of delivered as promised.

The primary use case for Snowflake is in our data warehouse project. We have a private DW and whoever has the credentials can access it. I am a data integration developer and we are using ETL tools to extract the data from different source systems and then load it in the data warehouse.

Snowflake is the latest technology. It has great flexibility whenever we are loading data and performs ELT (extract, load, transform) techniques instead of ETL.

This solution automatically performs micro-partitioning when the data is loaded. This creates a dynamic partition and based on the cluster, the performance is fast and really impressive.

Snowflake is using MPP, massively parallel processing techniques, which is a great feature. It saves developers time and allows us to focus more on client requirements.

It is difficult in some cases to perform ETL and this is something that should be included. As it is now, I use Informatica PowerCenter to load data from on-premises to the Snowflake cloud-based data warehouse. If this could be done by Snowflake directly, without an external integration tool, then it would become a full package. It would be awesome.

They do have a native connector to connect with integration tools for loading data, but it would be much better to have the functionality built-in. We would like to be able to just write an SQL query and do our work.

I have been working with Snowflake for six months.

We have not had any major issues with stability.

Snowflake does not require manual scaling because it does it for you. Developers just need to load the data and process the query. That's it. The developer's job is not to spend time improving performance, as it was with an on-premises solution. We had to do the partitioning, collect the stats, and everything else. In the case of this cloud-based solution, it doesn't require as much work. Instead, we can focus on the queries.

We are planning to increase our usage of Snowflake.

I have been in contact with technical support many times and it was awesome. I got great support. Whenever I needed anything they were ready to help me out, which was nice.

I have experience with Informatica PowerCenter and Oracle. PowerCenter uses ETL techniques instead of ELT. Oracle does not automatically perform micro-partitioning. Instead, you have to partition manually and it is a static partition.

Prior to Snowflake, I was using an on-premises data warehouse. Snowflake is the first experience I have had with a cloud-based data warehouse. It is an awesome tool.

There is no need to install this software, which is the best part. It doesn't require any maintenance, and although DBA support is required, it is much less compared to an on-premises solution. This type of cloud-based solution has no requirement for software, hardware, or maintenance because everything is managed by Snowflake's system.

The only assistance I had during the setup was from the integration tool, Informatica PowerCenter. This was used to export our on-premises data from Oracle and import it to Snowflake on the cloud.

You pay based on the data that you are storing in the data warehouse and there are no maintenance costs.

This is an awesome tool, but there is room for improvement in terms of integration. Also, in terms of management, nothing is perfect and everything can be improved.

I would rate this solution an eight out of ten.

We needed a data warehouse and we made a decision on what is the right tool for us as a data warehousing tool by comparing products. We looked into Microsoft Azure, Red Shift and Snowflake. In the end, we decided on Snowflake because it looks more up to date, it seemed much better purposed as a data cloud solution.

It was developed from scratch and dedicated to being used on the cloud and that was what we were looking for. It was not just an on-premises system which was then converted to use on the cloud. It was completely developed from scratch and purely focus on the cloud.

Because it was programmed with that dedication, it has some significant advantages.

The thing I find most valuable is that scalability, space storage, and computing power is separate. When you scale up, it is live from one second to the next — constantly available as you scale — so there is no downtime or interruption of services.

It has something like a time machine, as it is from Apple it incorporates that feature in a way similar to their operating system. So whenever you need a version of the data to test with, you can just go back and take a copy of what was backed up yesterday. It makes some things very easy. It backs up your data warehouses, so for example in our case, a colleague deleted a complete database and we just need to do an undrop on the database and the data was there again.

This helps you to have a development environment with current data. You can just clone your production environment and you have a development environment. Everything you do you can test it on real production data without destroying the production data itself.

These are significant advantages.

The company is constantly working to improve the product. Now they have a focus on data sharing, which is really great. We already share data with others who do not have Snowflake. That alone is already great. But if the other counterparts also have Snowflake, then it is extremely easy to share data. You can control access at low levels and even on the cell level. It is very secure.

With the improvements they continue to make, there is nothing now that I would say I miss or features that need to be added. Maybe there could be some more connectors to other systems, but this is what they are constantly developing anyway.

We have been using this product for two years.

The product is very stable. We never had an issue with stability. It is reliable and it is extremely fast. For example, we had a stock procedure that took half an hour to complete on our SQL cluster, and in Snowflake it was running in two minutes. So that is a significant time savings for just one task.

The number of people at our company currently using the solution depends on what we are trying to accomplish. We have four developers in Snowflake and then we also have users who are leaving data with us for our further analysis. That may be around ten other users.

With the growing data set we have and the increase in the size of our business, we will increase the use of Snowflake, but not with respect to the number of users. We are a small company and all the users who need to use it are already using it. We have more data that we need to load and which we want to integrate before we will make more usage of Snowflake.

There is nothing for us to complain about when it comes to technical support. The response time is really great. Whenever we have an issue there is some delay because they are in San Francisco in the United States so there is a time difference. But when we raise an issue, we get answers immediately. We may not get the solution immediately, as that is not always possible. But we get some type of immediate response and days later we have a solution. The tech support is quite responsive.

We use several products together for our framework. We have our data warehouse which is in Snowflake, we use Domo for standard reporting and we use R for data science analysis.

Before we had Snowflake we had a different solution. We switched to Snowflake because we felt the need to modernize our data warehouse architecture. We were also thinking about having other solutions in the cloud to reduce administration costs. With no effort on our part, we could have a stronger system compared to the effort and cost of doing a similar thing on-premises. This was the biggest advantage of Snowflake. We really do not need to have those administrative efforts anymore. Now we don't take care about when we run out of storage or that we need to buy better CPUs because if we need more computing power, we don't worry about it, we just use it and it is there.

The setup for the product was straightforward. For us, it was a little bit of a challenge because when we implemented the data warehouse, we also changed the architectural concept and we implemented a better framework. Because this framework was new to us it complicated our installation. But Snowflake itself, if you want to use and you have a data warehouse already in place with the right framework, then it is straightforward. You just store your data in and that's it. What you use on top is material for orchestrating all the load jobs. But this is other integrations and other choices that are really outside Snowflake itself.

The initial deployment from purchase until it was up and running in production took two months.

We had a consulting company help us for the initial two months of the setup and then afterward we did everything by ourselves. We were quite satisfied working with the consultants and they helped us to implement quickly. We mainly needed them because we implemented this metadata framework. In the beginning, we had this consultancy for analyzing our platform, which to select and which tools should be used. After we completed this initial portion of the project over the two months, we needed them mainly for completing the implementation of the metadata framework.

Snowflake itself is easy to learn. If you know SQL it is really not very hard. Everything is well documented and it is not a problem.

The whole licensing system is based on credit points. That means you commit to using it and you pay for what you use. You can also make a license agreement with the company so that you buy credit points and then you use them. So if you buy credit points that you think will last you for a year, you pay a certain amount of money and then you have these credit points available. What you do not use in one year can be carried over to the next year and it is that easy. The advantage of buying more is that you get a discount when you buy a bigger package with more credits.

There is not really much advice I can give people considering this solution except that they should use it and enjoy it. It really sounds simple but that is it. Of course, you need to be careful with the usage of your credit points. Because there are so many possibilities in configuring the way you build your data warehouse or infrastructure, the data warehouse might seem logical, but it is not the best with respect to using credit points. You need to be careful about this. It probably takes half-a-year experience and then you will know how to do it. If you don't know what you are doing, Snowflake also helps to optimize your usage so that you do don't use too many credits points. After one year, we realized we had spent a huge number of credit points and we talked to Snowfake and then they came to us and we analyzed our systems together and we optimized the usage.

On a scale from one to ten where ten is the best, I would rate Snowflake as at least nine. Why not a ten is only because maybe there is something better on the market which is a ten that I don't know about. For me, it is already a ten.