Snowflake Reviews

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 mainly used SQL scripts and provided a solution for different owners who want to query a database but have several tables. Typically, it is not an easy task to read several tables, so we provided our client with a very crisp data model where they can get results in a very quick manner. We implemented distribution as well as weekly partitioning. 

The relational piece and how one dimension relates to another just by using a key is the solution's most valuable aspect. We are managing everything by using simple relations. It's all about the relationships between dimensions.

Right now, we need to write code, but if they could create a version of Snowflake that was more drag and drop for those managers that don't know how to code, it would be great for our business.

The solution could improve the user interface and add functionality to the system.

I've used the solution for two years.

The solution is stable. We bring in incremental loads into Snowflake. There are pipelines that daily seed data from Oracle to a data warehouse. It's a prebuilt code and it allows for great stability.

It's very easy to scale because Azure cloud's own data warehouse gives us that capabilities to scale up or down at any time we want. There are a great number of users on the solution, but it differs from client to client. One client, for example, has about 30,000 users.

We've never been in touch with technical support.

The initial setup is straightforward. You just need to follow the documentation.

We handled the implementation ourselves. I've handled two or three projects previously, so I'm comfortable with the solution. We don't need assistance because we handle the consulting part.

The solution is deployed on the cloud using Azure, where there's a data warehouse. We primarily use SQL scripts.

For those considering implementing, I'd advise that they understand the business very deeply first. Not every business would have a demand for Snowflake, so it's not for everyone. It's important to understand the requirements and then, if it makes sense, to implement Snowflake.

I'd rate the solution eight out of ten. I'd rate it higher if it had a better user interface.

We primarily use the solution for data warehousing.

The entire managed service operations for the solution is great. Snowflake does everything for us. Whatever version they have, they implement the latest for us; we don't have to worry about any versions, any upgrades, anything else because they handle it.

The solution should offer an on-premises version also. We have some requirements where we would prefer to use it as a template. 

The integration capabilities could be improved.

The solution has been very stable for us.

We have not tested scalability, but the solution claims that it's scalable. It's on the cloud, so I imagine you could scale rather easily if you needed to. 

They separate compute and storage. You can scale storage independently of the computer, or you can scale computing independently of storage. If you need to buy more computer parts you can add new virtual warehouses in Snowflake. Similarly, if you need more storage, you take more storage. It's most scalable in the database essentially; typically you don't have this scalability independence on-premises. 

We have about 40 people using the solution. They're mostly business users.

Technical support is good. Occasionally, they take a bit of time to resolve issues, but other than that they are okay. We're mostly satisfied with them.

We're system integrators, so we use different solutions including SQL Server Data Warehouse and Greenplum as well as Snowflake at the moment.

I've used many data warehouse solutions, including Hadoop, and Oracle SQL Server Data warehouses. I switched from those to Snowflake because Snowflake is on the cloud and gives you separate computing and storage scalability, which Hadoop is unable to offer.

The initial setup is straightforward. There's no deployment; it's just your code solution that needs to get up and running. You have a deal with Snowflake in terms of what environment you want, and when you want to use it, and they'll set it up within a day for you.

Snowflake helped us with the implementation.

We are system integrators, so for all our customers, we offer different solutions.

We only use the cloud deployment model. Snowflake doesn't offer on-premises deployments.

Snowflake on cloud is the best right now. There are only a few other options. Redshift is not scalable. With SQL Data Warehouse the concurrency is an issue, as well as scalability. Also, it does not have all the features that you see in an on-premises SQL Server.

Snowflake a good database. I'd recommend the solution to others.

I'd rate the solution seven out of ten. We are still new to the solution. There are a few things we still have to explore before we would give it 10. Typically, I come from a Hadoop background, so compared to Hadoop I think everything looks good before the data warehouse side. We're quite pleased with Snowflake and moving from Hadoop into Snowflake has been a very good transformation.

We are an IT Analytic Consulting company and we work with many different products. We have Snowflake and a Snowflake account mainly for education purposes and our internal training.

We connected it to different sources, mainly internal sources. Most of them are on-premises and some are on the cloud.

The deployment model is public.

The most valuable features are: 

The multi-clustering: being able to access stored data without contention.

Virtual Warehouse (VW) sizing: Change the size of your VW on demand. 

Zero copy clone: Easy to create development and test environments.

I would like to have a tool where you can easily see the price because they need clarity of pricing.

Support needs improvement, as it can take several days before you get some initial support.

Integration could be the key to provide an optimal solution.

In the near future, I would like to see a built-in basic analytics solution that can be embedded for testing purposes, so you can see data not only in tables but also in a graphical way in order to better prepare data for analytics.

Embedded analytics would be nice.

The scenarios that we are using are not complex. For what we are using it's pretty stable.

With a different cloud that warehouses are the standard for now but the scalability is pretty straightforward.

In terms of support, it can take some time as there are not many people to provide support. Compared to other more stable providers it's a bit slower.

You have to wait several days to get support.

Snowflake is not the only solution we are working with but it is the only solution that we are heavily focusing on and investing our efforts into the knowledge and the training.

The initial setup can be complex at the beginning but once you get into it, it can be straightforward.

When you come from an on-premises solution and you have to change or shift to the cloud, it works very differently. Once you know the differences then it is straightforward.

We did not implement this solution through a vendor, we did it ourselves.

Pricing can be confusing for customers. For example, if a customer is asking for an estimate of the price, it's hard to tell because it is not easy to measure.

Improvement on the pricing and how it is presented is needed.

I would suggest being careful with selecting resources. Each customer case can be completely different and each can require different resources.

It's not only the database itself but also how you integrate it with the analytics and the resources. The estimation of the resources is something that you have to pay a lot of attention to when selecting the resources because sometimes you will need EPL or ELT integration, which requires a tool, as does analytics.

For an end to end solution, you have to include other products.

I would rate this solution an eight out of ten.