Snowflake Reviews

We use Snowflake for data warehousing.

We would like to see more security including more masking and more encryption at the database level.

We have been using Snowflake for three months.

Stability-wise, this product is good.

Snowflake is quite scalable. We have four people who are using it.

So far, technical support has been good.

The initial setup is very simple.

My advice for anybody who is implementing Snowflake is to start small, then prove out the value and you can grow.

I would rate this solution an eight out of ten.

I work as a data scientist and our primary use of Snowflake is for machine learning.

Recently, we were trying to extract data to determine the best configuration settings for one of our products.

As it is SQL-like, it is easy to write queries.

The querying speed is fast.

We would like to have an on-premises deployment option that has the same features, including scalability.

I have been working with Snowflake for six or seven months.

From what I have seen and heard, I think that Snowflake is pretty stable. I haven't faced any such problems, myself. I am not aware of the entirety of the lifecycle, but I haven't heard any complaints.

My impression is that this product is pretty scalable.

I have not been in contact with technical support, although my team has been and they are okay with it. My impression is that they are good.

The pricing for Snowflake is competitive.

My advice for anybody who is considering implementing Snowflake is that from a user's standpoint, it is a good product. Having a database in a cloud setup means that you don't have to scale and it has got many features already included.

For our use case, we found this Snowflake was good enough and did not need any enhancements. I recommend using it.

I would rate this solution a ten out of ten.

We primarily use the solution in order to have the daily transactions of trades. It's to manipulate and find out the benchmark of every broker and institutional manager.

The solution's most valuable aspect is the ability to process the bulk amount of data and try to clone the database. We try to clone the production database. Instead of syncing the whole database, we can just clone it up and start working on it. Basically, the cloning and the database are very user-friendly.

The solution is very stable.

Right now, Snowflake doesn't have any analytical functions, especially in comparison to Oracle and other databases. The analytical performance needs to improve. It would be ideal if Snowflake was able to use the analytical functions, and what we have in the relational database. That would be really helpful. 

They don't have any SLAs in place. It would be better if they did.

I've been working with the solution for two years now. The company, however, has been using it for three years at this point.

The solution is quite stable. It's reliable. It doesn't crash or freeze. There aren't bugs or glitches.

The solution is definitely scalable. We're able to add nodes to grow it out when we need to. If an organization needs to expand the solution, they can do so easily. We find it to be very reliable.

There are about 300 people using the solution at this time. We don't plan on increasing usage at this time.

Technical support is very, very good. It's a responsive and knowledgable team. We're quite satisfied with the level of service we receive.

That said, Snowflake technical support doesn't have any SLAs. If they had a small amount of SLAs, then it would be helpful for us to clear or solve any production issues, etc. that we may run into.

We need about 50-60 people to maintain the solution.

Snowflake's pricing is a bit higher than other competitors.

We were looking at Amazon Redshift previously. However, we decided that Snowflake was more reliable and scalable.

We're a customer. We don't have a business relationship with the solution.

Users considering adding the solution should understand that Snowflake can be used only for transactional processing, not for analytical processing. If they want to go for transaction processing, they can go for Snowflake and if they want to go for analytical processing, they should look at or go for an Oracle database.

I'd rate the solution seven out of ten.

We use the solution for data. We like that there are so many different formats and many structures for analysis.

The architecture we'll be using due to being on the cloud will assure we have less to do. There will be no indexing, for example. Everything's managed by the servers. That way, we can focus on the data warehouse and on the data.

From a data warehouse perspective, it's an excellent all-round solution. It's very complete.

The user interface continues to be an issue, especially when we need to get data out of Snowflake. It's very easy to get data in, but it's not too easy to get it out or extract it.

It would be nice to have some built-in solutions that would solve. for example, how to delete data from a customer when they request it.

There needs to be stronger data protection.

I've been using the solution for just a bit less than a year at this point.

Our clients have been very impressed with the solution's overall stability.

The scalability is incredible. It's the best I've ever seen. Organizations can scale easily. I can scale up four times faster as well. Something that usually takes 60 minutes can be done in 15 or 20 minutes. It's faster and I save costs because I only pay for the time. Even though I'm paying "more" I end up saving money with this time based costing.

I've only contacted technical support a handful of times. I have, however, found them to be very savvy product-wise and very helpful. Their technical support staff are all experts. They know the product extremely well.

The initial setup is very straightforward. I wouldn't describe it as complex.

How long it takes to deploy depends on your knowledge and your background. It's difficult to judge. I've been working for 20 years now with data warehouses. For me, it was very easy because of my extensive background. However, it depends on what someone knows, and their technical background. It can be difficult for others who maybe don't have as much knowledge or first-hand experience with warehouses.

We're partners with Snowflake. We support our customers and can help them implement it as necessary.

The solution has an excellent pricing strategy. The costs are open and transparent. If you don't use it, you don't pay for it. It's that simple.

We're partners with Snowflake.

The difference between Snowflake, and, for example, Azure, is that there is real separation between the computer and storage. Snowflake is the only one that's really separate and it's much simpler to scale or shift data. It makes everything much easier.

One of the best options on the market right now is to have a cloud-only setup. Not everyone is using the cloud, but everyone will catch up.

I'd rate the solution nine out of ten. If the user interface was better and they had a few more features and did some useability tweaks it would be perfect. Also, it's hard to get the data out of Snowflake, and that's a real issue design-wise.

We use this product basically for developing an IoT (Internet of Things). Currently, we are sending data from our S3 (Simple Storage Service) storage. In the future, we are planning to directly stream data to Snowflake.

In terms of features, we have not yet explored the product completely. So we are still in the proof of concept phase. As of now, the product meets our preliminary requirements. The snapshot feature is good and the rollback feature is good. That is why we have the product and these are the key things we need.

The recovery process is very simple and very user-friendly as well. The constraint files could be improved. But the most important things are there. Also, the interface is good to work with and user-friendly.

If I had to say what needs improvement, in my experience is that the availability is a problem. Availability should be high and has to be enhanced.

I still have not explored all of the existing features. Because I have not been deeply involved with using the program it is hard to say what else is missing or what I would need.

We have just explored the product for a few months.

The stability of Snowflake is very good.

Scalability is very good and very simple.

Within the company, we currently have a total of fewer than 50 people using the product. Their general roles vary from data analyst to data scientist, to IT professionals, and maybe one or two of the upper managers.

I tried using technical support once and they were very helpful. But after that, I have not had any reason to explore the support services.

The initial setup was simple.

The implementation was done by the vendor.

Before choosing to work with Snowflake we looked at virtual solutions and we looked at Redshift, we looked at Qubole and a couple of other cloud options. Earlier when we did a mining site, I was working with Alteryx, so I was already familiar with that product and its capabilities to use for comparison. We decided to go with Snowflake because it seemed mature and had what we wanted.

My advice to someone who is looking at Snowflake is that if they are looking at analytics tools in addition to warehousing and certain advantages of cloud computing, then I would suggest Snowflake. But if they are just looking for the warehousing part where you will later just use another solution on top of it, then I would not suggest Snowflake.

On a scale from one to ten where one is the worst and ten is the best, I would rate Snowflake as an eight or nine. Let's say 8.5.

The primary use case is big data warehouses.

• Excellent performance
• Very easy to use
• Amazing UI

The most valuable feature is the snapshot database. In one second, you can just take a snapshot of the database for test purposes.

One year.

Basically, it is not cheap.

We are a big data company. We have many thousands of devices deployed from our customer base. These devices upload data, on an hourly basis, to a central storage. Next, we run some ETF processes that crunch and process data, then we store that data in a structured way on Snowflake.

Over the past six months, it has been more of a development project.

I am using the latest version.

• I like the idea that you can assign roles and responsibilities, limiting access to data. That has been very interesting to us. 
• The robustness of the system is very useful to us. 
• The availability of the system. 

We would like Snowflake to be able to do inter-cloud migrations. That would be great. I want to be able to switch clouds.

Six months.

It is stable.

If you go with one cloud provider, you can't switch.

We have very few users. There is just a very limited number who are mostly developers. We did not roll out the end product. We did not roll out product and services based on that foundation/infrastructure yet.

I have not personally contacted technical support.

We previously used HPE and Microsoft Insight. We switched to Snowflake for the availability, security, and loading times.

The initial setup was very straightforward. It was very quick. The complexity came from our specific use case scenario.

We also looked at HPE and Microsoft Insight.

Analyze your user scenario. If your scenario is managing large amounts of data in extremely, different environments in a structured way, then this is a good option.

I would rate this solution as an eight (out of 10).

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.