We compared Snowflake and VAST Data based on our users reviews in five parameters. After reading the collected data, you can find our conclusion below:
Comparison Results: Snowflake is praised for its easy setup, valuable features, and good customer service. However, it needs improvement in areas like pricing transparency, data integration, user interface, and documentation. On the other hand, VAST Data is commended for its simple and efficient setup, strong failover capability, and good customer service. It could benefit from enhancing its read/write ratio. The pricing perception and user ROI differ for both products.
"Its performance is a big advantage. When you run a query, its performance is very good. The inbound and outbound share features are also very useful for sharing a particular database. By using these features, you can allow others to access the Snowflake database and query it, which is another advantage of this solution. It has good security, and we can easily integrate it. We can connect it with multiple source systems."
"The solution's computing time is less."
"Great scalability and near zero maintenance."
"The solution's customer service is good."
"The querying speed is fast."
"The most efficient way for real-time dashboards or analytical business intelligence reports to be sent to the customer."
"It is quite easy to manage."
"The best thing about Snowflake is its flexibility in changing warehouse sizes or computational power."
"This has been one of the most reliable storage systems that I have ever used."
"The solution is useful for machine learning and scientific applications, including computer simulations."
"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."
"The data science functionality could be improved in terms of the machine learning process."
"An additional feature I'd like to see is called materialized views, which can speed up some run times. I'd like it to be able to be used where you can have multiple tables inside them; materialized view. That would be nice. As well as being able to run cursors, to be able to do some bulk updates and some more advanced querying, table building on the fly."
"To ensure the proper functioning of Snowflake as an MDS, it relies heavily on other partner tools."
"It would benefit from an administration that allows you to be aware of your credit consumption once you have the service so that you may be sure how many credits you are consuming when you use the platform and to make sure that you are making the most efficient use of these resources. In other words, to improve their interface so that you may monitor the consumption of your credits on Cloud."
"It's difficult to know how to size everything correctly."
"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."
"It needs a bit more rigor and governance, which is something you don't get with newer tools. This makes it less enterprise scalable. Its governance and structure can be enhanced, which would really be valuable. I would like to see some kind of prebuilt functionality in terms of having almost like a pre-built data warehouse. A functionality for generating automated kind of pieces would be good."
"The read/write ratio is an area in the solution with some flaws and needs improvement."
"The write performance could be improved because it is less than half of the read performance."
Snowflake is ranked 1st in Data Warehouse with 94 reviews while VAST Data is ranked 8th in NVMe All-Flash Storage Arrays with 2 reviews. Snowflake is rated 8.4, while VAST Data is rated 10.0. The top reviewer of Snowflake writes "Good usability, good data sharing and elastic compute features, and requires less DBA involvement". On the other hand, the top reviewer of VAST Data writes "Stability-wise, a device that has been up and running for years". Snowflake is most compared with BigQuery, Azure Data Factory, Teradata, Vertica and AWS Lake Formation, whereas VAST Data is most compared with Pure Storage FlashBlade, NetApp AFF, Pure Storage FlashArray, Qumulo and DDN Storage Fusion Architecture NVMe.
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