Snowflake Reviews

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 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.

Our aim was to migrate everything from on-premise, so we just migrated as it is and then we had issues. Some use cases that were running on-premises were not installed. We just went through each case and then finalized the issues with some of the packages that were not working or some users that were not getting what they were expecting. We did deep analysis on each and every case and then looked for options in Snowflake and are now working with the team to move everything over to Snowflake. 

The data warehouse is one of the great concepts of Snowflake. The coding plans are also a great feature. You can switch out the values or sizes. 

It would be helpful if implementation could be handled more on the user-side. We need to train the users on best practices and how to use the solution properly. It's a cost issue. If they don't run it properly then it'll end up costing more money.

There are some stored procedures that we've had trouble with. The solution also needs to fine-tune the connectors to be able to connect into the system source.

The solution is stable. We had only one failure, but that was because of AWS issues. Beyond that, I haven't seen anything else. From the Snowflake side, within 10 minutes they reported the AWS issue. It was under two hours of downtime because of the quick response.

As long as you don't need to worry about storage or cost, this solution would be one of the best ones on the market for scalability purposes. We've migrated about 400-450 dealers onto the solution so far. We do intend to expand usage so there will be more users and more data. The drawbacks we've had with on-premises was space being a constraint and the user code having limitations.

Customer support is good. There is always someone who's going to respond. They will let you know what can be done and what is possible.

We did some testing and some comparisons, but it's all set up now and running fine. The deployment took about three months. Since we didn't want to disrupt the on-premises, or overload the system, we did most of the migrations on the weekend.

For maintenance, in the beginning, until you are through with training and performance tuning, you will need more people. You might need to start with seven or so, and then, for ongoing work, probably one or two people can manage it. 

We had a Snowflake consultant on-site that assisted us with the implementation.

It's an expensive solution. We can't predict exactly how much until we've streamlined everything and the user requirements have been completed, but normally they charge on the storage, which depends upon the average storage amount used for the month.

We looked at IBM because it also has on-premise solutions. We also looked at Azure as well as AWS.

Because most of the issues you come across can be dealt with on the user's sites, it's important to educate the users and understand their requirements.

The best advice I can give is to understand the product and to try to stick to what is required. From the business side, you need to monitor usage and monitor the space because of on-premises constraints. If it gets filled up then you will have to react. However, this solution is very scalable. 

I would rate this solution between seven and eight out of ten. The solution still has some constraints that need to be addressed.

We use the solution for data storage and integration purposes.

The solution's most valuable feature is path application.

They should improve the performance of the solution's transaction application.

It is a stable solution.

We have 20-30 solution users in our organization.

The solution's customer service is good.

The solution's initial setup was very straightforward.

The price for the solution's license depends on the use cases.

I recommend the solution to others and rate it as a nine. It efficiently processes the data and gets reports as well.

We use Snowflake as a data warehouse and analytics platform. I'm a solution architect and we are customers of Snowflake. 

It's very easy to use, easy to query, and it provides pretty accurate results. It's a market leader. 

The price could be reduced, it's quite high.  

We've been using this solution for about three months. 

The solution is stable. 

The solution is highly scalable. 

I haven't used the technical support. 

The initial setup is very easy, especially if you have cloud knowledge. We have around 150 users. 

We moved from Red Shift to Snowflake because of scalability and the independence it provided. 

I rate this solution eight out of 10 and recommend it to other users. 

We are using the Matillion as the ETL tool and Snowflake has storage and there is no data warehouse component for storage.

I like the fact that we don't need a DBA. It automatically scales stuff.

Snowflake has better performance features; it automatically knows the difference between the data volume. It adjusts itself.

The performance is great. It internally optimizes well.

The product is stable.

The solution is scalable.

There are certain special features that are not available. For example, in Oracle, we have an SQL field. We have functions, procedures, packages, et cetera, which you can create similarly in Snowflake. However, it's not that flexible when compared to Oracle.

I've used the solution in the last year.

The product is stable and the performance is excellent. There are no bugs or glitches. It doesn't crash or freeze. It's extremely reliable. 

Snowflake scales well. If a company needs to expand, it can do so.

We also use Matillion. I find Snowflake a bit better.

We're partners.

While I can't speak to the version number we are using, we're always on the latest version of the solution.

Snowflake is a good product. It is quite robust and scalable. However, a few of the functions are a little complex in Snowflake. 

I would rate the solution at a nine out of ten.

We are using it as a data lake. We are using it as a data warehouse and a data mart. It is basically the entire BI and analytics platform.

I am using its latest version.

We find the data sharing and data marketplace aspects of Snowflake absolutely amazing.

There is a scope for improvement. They don't currently support integration with some of the Azure and AWS native services. It would be good if they can enhance their product to integrate with these services.

It would also be great if it can support stored procedures.

I have been working with it for four years.

It is stable.

It is scalable.

You need to be aware of the bloating costs. It is easy to use, but if you don't use it wisely, then your monthly bill can bloat a lot. You need to be a bit aware of its consumption cost.

I would rate it a seven out of 10.