Snowflake Reviews

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.

The ETL and data ingestion capabilities are better in this solution as compared to SQL Server. SQL Server doesn't do much data ingestion, but Snowflake can do it quite conveniently.

They need to improve its ETL functionality so that Snowflake becomes an ETL product. Snowpipe can do some pipelines and data ingestion, but as compare to Talend, these functionalities are limited. The ETL feature is not good enough. Therefore, Snowflake can only be used as a database. You can't use it as an ETL tool, which is a limitation. We have spoken to the vendor, and they said they are working on it, but I'm not sure when they will bring it to production.

They should also make its initial setup easier. Its customization and configuration are not very straightforward.

Their technical support is awesome, but it is just too expensive.

I have been using this solution for about two years. I am currently using its latest version.

It is very stable.

It is very simple to scale up and down depending on the project or situation, which is an advantage.

They are fantastic but just too expensive. They charge hourly rates and are very expensive.

Its setup is not very straightforward. Its customization and configuration are not very straightforward. For two large data factories, the configuration is too complicated. They should work on it.

It is a good solution. At the moment, I can't find another product that is better than Snowflake, but it needs better ETL functionality, easier configuration, and cheaper support. All products have got some limitation.

I would rate Snowflake an eight out of ten.

It was used in my previous company for a massive data warehouse. It was used for events and actions from other data sources. We had its latest version.

It is a very well-distributed system. It has different data engines for different applications. Many applications can use different computational engines at the same time. In terms of data processing, the feeling was similar to working with a relational database but in a scalable way.

The scheduling system can definitely be better because we had to use external airflow for that. There should be orchestration for the scheduling system. Snowflake currently does not support machine learning, so it is just storage. 

They also need some alternatives for SQL Query. There should also be support for Spark in different languages such as Python.

I worked on it a lot in the past 12 months in my previous company.

Its stability is absolutely great. There are no problems with its stability.

It is scalable. There are no problems with the scalability of this solution. There were 50 or 60 users using it at the same time.

I don't have much experience with their technical support. When we asked them some technical questions related to Spark integration, they were quite supportive. Their support was fine.

I have used BigQuery on Google Cloud Platform and Spark on an internal cloud.

It was quite straightforward. There is no problem with that. However, managing the database and roles and access is complicated. Its deployment didn't take a long time.

I would rate Snowflake an eight out of ten.

We use the solution for data warehouses and data modeling.

I have found the solution's most valuable features to be storage, flexibility, ease of use, and security.

There is a need for improvements in the documentation, this would allow more people to switch over to this solution. I would like to see in the future a wizard for data modelization automation.

We have been using this solution for approximately one year.

The solution is stable.

I have found the solution to be scalable. We have a few employees working on this solution in my organization.

The solution is a SaaS, it can be installed and managed by your provider. The installation setup is not difficult in this case. However, the configuration took us a couple of days.

We did the configuration of the solution ourselves. You need a data engineer and modeler for the movement of information into the solution.

There is a licensing for this solution and we purchased an enterprise license. Overall the solution is cost-effective.

We did evaluate some other solutions previously, such as Snap Analytics. All the different solution have their pros and cons. However, many are moving to this solution because it is in the cloud.

I would recommend this solution to others and we are going to keep using the solution in the future.

I rate Snowflake an eight out of ten.

We have used Snowflake as a data warehouse solution in one of my projects and as a combination of data lake and DWH for another project.

In the second project, we migrated from a SQL DB to Snowflake as the DB was becoming a bottleneck in terms of storage and also in speed of execution of the queries as the data was growing. We also have JSON, which is hard to store and process in a SQL database. This is something that is handled beautifully by Snowflake.

In the first project, we used Snowflake as a simple DWH to store and process data. Also, as a BI reporting source.

Snowflake helped us to improve query performance as the data was growing. Also, we could store and process JSON and XML using Snowflake, which was not possible with RDBMS solutions. This also helped us to store huge amounts of data in Snowflake as a single source of truth and we could also use it as DWH. It is a single technology for multiple use cases.

Snowflake also helped us improve query performance to a great extent. The inserts of large JSON objects are very quick and processing them is very easy.

The most valuable features are:

1. The Virtual Warehouse and separate storage is definitely one of the best features. It automatically scales the warehouse up and down as per the usage.
2. Processing semi-structured data like JSON and XML has helped reduce a lot of coding that was needed earlier.
3. The speed of execution is definitely good.
4. There is zero maintenance activity required from users on the database, which is a big plus.
5. Working with Parquet files is supported out of the box and it makes large dataset processing much easier.
6. Automatic scaling up and down.

Several areas need to be improved, as follows:

1. Cost reduction: This is always good to have, and nobody would say no to it.
2. Implement multiple result windows as tabs to compare results. If we can have a feature where the results can be moved to different tabs, so that I can compare the results with earlier queries before applying the changes, it would be great. Also, it should be optional, where it can be enabled or disabled as needed.
3. I would like to be able to copy the results onto the clipboard and paste them directly into Excel.

We have been using Snowflake for two years.

We have a data mart, and we are using it to share data with big enterprise customers with major security requirements.

Snowflake is an enormously useful platform. The Snowpipe feature is valuable because it allows us to load terabytes and petabytes of data into the data mart at a very low cost. Then we just share it out, and all the compute expenses are charged directly to our clients.

It would be better if they had a data profile tool that tells me where the gaps are in my time series data. We are anxiously waiting for them to release their data catalog and analytics capabilities, which is going to happen in June or July. If that works the way we think it might, then that would just extend our firm's capabilities into a space that we have never been interested in building ourselves. It could be a really good thing for us.

We started using Snowflake this year.

There's never any outage, and it's cross-cloud. The stability is not even a good question for that platform. It makes no sense to us.

Snowflake is scalable. It does cost more money, but it's some kind of magic they're doing behind the scenes that you don't have to think about. It's brilliant, and it's going to take over completely.

Their tech support is good. Their sales team is very technical, and they're able to speak to our engineers and walk them through what we need to do. 

About three years ago, Databricks was sort of the hot thing among our clients, and everyone was using it for low-code analytics. We had to deliver data in a format that was specific to Databricks. Databricks had this massive growth, use, and adoption. They have a very good footprint now, but we see those same clients shifting their data to Snowflake, and pretty much nobody asks for Databricks anymore.

I think there's this big war sort of brewing between Databricks and snowflake. Snowflake is going to come out with the analytics capability that Databricks has. They're working furiously to get it released. I don't know what it's going to look like, but they're going head-to-head with Databricks. I think Snowflake is going to crush them.

In the beginning, we didn't know what we were doing, and we racked up huge compute costs, shockingly and quickly. But the sales team was extremely helpful and showed us where we were doing everything wrong, and they explained to us how best to use their platform. We have massively funded data engineering teams, but now our use has plummeted to almost free.

Because of the caliber of our customers at the time, we had to sign on to the enterprise subscription tier. We're a startup, and we didn't know it at the time, but the cost per credit for the enterprise tier was almost double. 

The cost per credit, that's where you get all this unlimited autoscale that you don't even have to think about. We don't really need any of that because they already provide all the redundancy, backup, failover, and all of that stuff. We scaled down and cut all of our costs almost in half by getting rid of that scalability capability because we don't need that.

They give a different price for every single company. I don't know if I negotiated that well, but we got the enterprise tier for $3 a credit, and the other two were a dollar-ninety a credit. I suspect we don't have almost zero compute usage, but I know that our annual contract packages are below all of their minimums.

On a scale from one to ten, I would give Snowflake an eight.

The solution is mainly used for analytics in data warehouses. We are independent consultants and customers of Snowflake. 

The scalability of this product is great and the fact that it has a so-called zero clone copy and is near zero maintenance is also great. There are a lot of good features, it's a very sophisticated, cutting edge technology and is super easy to use. They are developing the platform very, very quickly so there are plenty of new features implemented all the time. You can concentrate on implementing things in Snowflake without tuning or configuring it.

There are some functions in the SQL language in other products which are not yet included in Snowflake's SQL. It would be helpful to have those included, they're nice features. It's a minor issue because all those things can be implemented in some other way. Not essential, but it would be nice to have them. 

I've been using this solution for 18 months. 

This is a stable solution and the maintenance and updates are automatic. Snowflake is responsible for that.

I have been quite satisfied with the technical support.

The initial setup is very simple, just go to the internet and start using it. Of course, if it has to implement to part of the customer's own cloud infrastructure, then there are more steps to configure. We provide that service for our customers. 

Everything is included in the license fee which is mid-range in terms of pricing.

The advantage of Snowflake is that you can focus on implementing things in Snowflake without tuning or configuring it. That's the advantage of this solution compared to others. Many other data warehouse solutions need some kind of maintenance or database administration, and that takes time. The extra time means you're being taken away from other things and in that regard, Snowflake is an absolutely great product.

I think the solution is suited to big companies because they tend to have lots of data. The more data you have, the more you need power and scalability to process it. I would recommend finding a good partner already familiar with the solution for implementation. It's good to have someone familiar with the architecture.

I rate this solution a 10 out of 10.