Snowflake Reviews

We have different data models established on Snowflake so our primary use case is to store data from different sources, such as Azure Data Factory, or Databricks. We use it to create the data coming from different sources, and then we store the data. In addition, we also have a reporting structure that we use. We are partners with Snowflake and I'm a lead data engineer. 

The most valuable feature of Snowflake is the Mbps they have established because it's quite a bit faster than any other data warehouse. The solution has different warehouse sizes in place, and we're able to switch through and choose what we want. It can be done in one or two seconds. In other data warehouses, it may take around one minute to set up a different configuration. In Snowflake, it can be done in, two or three seconds. And apart from that, the most important thing given that I have to analyze all this, is that it's very good with the time travel, it's a great feature. 

One thing which I believe Snowflake needs to improve is related to product activation queries. It's not possible to change the warehouse size while executing. It means, for example, that the query is sometimes activated on a larger surface even if I've switched to extra small, the grading in the background is running on extra large. The result is that I have to pay for extra large until the execution is complete. The cost implications can be quite large. There should be a system where they provide a prompt so you can know the current warehouse size.

It would also be helpful if they would simplify the process of using Snowpipe. The way it works now is quite complicated. There are certain steps that you have to follow which is fine but if they could simplify that process, it would be helpful. 

I've been using this solution for a year. 

I've only had one issue related to stability in the past year. 

It's a scalable solution, we have unlimited storage in Snowflake.

The technical support is quite good. We've used them when we've had to implement something and we need some guidance.

The amount of data which we are currently handling, cannot be handled yet in any other data warehouse, but we do have experience with Azure Data Warehouse. We don't have to manage anything with Snowflake, but with Azure we do. Snowflake is much faster, and I believe it is cheaper as well. They have developed it on top of their own system and integrated the concept.

The initial setup is straightforward. It doesn't require any hardware. It's just about getting the account access and having a browser. Everything is done by Snowflake. There is a set process that you need to follow. It is a really fast process, and it helps that the entire migration can be done within minutes. The solution is used on a daily basis by hundreds of people. 

It's pay-as-you-go with Snowflake. The cost is around $US 50 per DB. Terabyte is around $US 50 per month. There are no additional costs. They are divided into two steps to assist the computer power as well as the storage power. Computation cost is relative to the warehouse size. However long our warehouse is up and running, we are charged.

I would definitely recommend this solution. 

I would rate this solution a nine out of 10. 

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.

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.