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 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).

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.