Snowflake Reviews

We use it for presentations to clients. 

The syntax is advanced which reduces the time to write code. 

They should improve the reporting tools. 

They could increase their bandwidth to connect to other ETL tools. 

I have been using Snowflake for around six months. 

The stability is good. There is no performance downtime. 

If there is a need for scaling the setup is not so good. 

Their support is good. 

The initial setup was not complex. We needed a dedicated person for the setup. Once we know the requirements, it's not that complex. It has straightforward parameters. 

I would rate Snowflake an eight 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 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.

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.

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 were using MySQL and MongoDB for our regular operations but when we grew, we were forced to handle a huge number of datasets. We could have petabytes of data in and out on a regular basis. We struggled a lot to complete the operations in a timely manner. With Amazon Redshift, we gained a lot in terms of timing, as well as project completion. Even-through we are happy with Redshift, in terms of pricing and availability of nodes, I am more comfortable with Snowflake. Some of the scoring mechanism really works well in the distributed architecture of Snowflake.

• Scalability. This solution has the ability to load a huge number of datasets (I have experience with petabytes of data) and process them. Storage is not limited, and we can increase what we want.
  
• Performance. The distributed architecture of Snowflake has the capacity to process huge datasets faster and allows us to scale up and down according to our needs.
• Flexibility. This feature is helpful for the user to increase the node size and config depending on their need. There is no need to wait for hardware to be in place whenever we increase the dataset. Snowflake provides the option to increase the node or cluster size whenever required.
• Multi-formatted accessibility. The Snowflake engine has the capability to read the following file formats: CSV, DELIMITER, FIXEDWIDTH, AVRO, JSON, BZIP2, GZIP, LZOP. The user can choose which format is best for their requirements.
• Configuration. Even though its running in the AWS platform, it beats their platform product. I feel more flexible with this solution than I do with Redshift.
• Snowpipe. Snowpipe is a better system to feed stream data to the Snowflake database.
  

Snowflake has to improve their spatial components since it doesn't have much in terms of geo-spatial queries.

No

No

It's really good. I am happy with the product and the service.

With Amazon Redshift, we gained a lot in terms of timing as well as project completion. Even through we are happy with Redshift, in terms of pricing and availability of nodes, I am more comfortable with Snowflake.

The initial setup of Snowflake is very simple and straightforward. We do not need to read or understand any of the technical documentation. It is a plug-and-play service or platform.

I have implemented this solution through an in-house team.

I can't directly convey ROI because we are not using only Snowflake. We are using multiple products to increase our revenue and decrease time consumption. This makes it difficult to calculate ROI.

I have experience working in Hadoop & Redshift as well. When I compare the three (Snowflake, Hadoop, and Redshift), Snowflake is more user-friendly in terms of configuration and maintenance.

We are using it for optimizing costs and using financial data.

It is a cloud solution with many useful features. It has the data science capability. It can transform data and prepare data for a data science project with scalability.

We would like to be able to do modeling with Snowflake. It should support statistical modeling.

I have been using this solution for more than a year.

It is stable.

It is very scalable. We currently have more than 50 users. We can increase its usage.

I have not contacted their support.

I used Cloudera One about two years ago.

It is easy. It is a SaaS solution, so there is no installation. Therefore, you don't need the infrastructure team, but you need a few data analysts.

It is pay-as-you-go. Its cost is in the medium range.

I would rate it a 10 out of 10.