We performed a comparison between Snowflake and Vertica based on our users’ reviews in five categories. After reading all of the collected data, you can find our conclusion below.
Comparison Results: Vertica has an edge in this comparison due to its excellent performance. Snowflake does come out on top in the Ease of Deployment category, however.
"All the people who are working with Snowflake are extremely happy with it because it is designed from a data-warehousing point of view, not the other way around. You have a database and then you tweak it and then it becomes a data warehouse."
"This is the advanced version of the cloud version, so it's really a flexible tool. If you have it implemented at home, you can access it from anywhere."
"The features that I have found most valuable are the ease of use, the rapidness, how quickly the solution can be implemented, and of course that it's been very easy to move from the on-premise world to the Cloud world because Snowflake is based on SQL also."
"The solution is stable."
"The most valuable feature has been the Snowflake data sharing and dynamic data masking."
"We find the data sharing and data marketplace aspects of Snowflake absolutely amazing."
"Can be leveraged with respect to better performance, auto tuning and competition."
"Snowflake is scalable both in terms of the amount of data that you can run through it and the number of users that engage with it."
"Vertica enabled us to close large deals. Customers with large data sets had to be migrated from PostgreSQL to Vertica due to performance."
"Allows us to take volumes and process them at a very high speed."
"The solution has great capabilities. The tool that instructs the internal database forward is easy to use and is very powerful."
"It maximizes cloud economics with Eon Mode by scaling cluster size to meet variable workload demands."
"It has improved my organization's functionality and performance."
"The solution is quick, has good compression data, and is not expensive."
"DBAs don’t need to add a partition every month/quarter like with other DBs."
"Speed and resiliency are probably the best parts of this product."
"From the documentation, the black box is not very descriptive. Snowflake does not reveal how exactly the data is processed or sourced."
"Their UiPath, the workspace area, needs some work."
"The data science functionality could be improved in terms of the machine learning process."
"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 complexity of the initial setup of Snowflake depends on the use case. However, Snowflake itself, we don't set it up. The difficulty comes from the ingestion patterns, depending on what data I'm putting in, what kind of enrichment, and what additional value we have to add. However, it does tend to get complex because we have a lot of semi-structured data which we need to handle in Snowflake. There have been some challenges."
"It doesn't enforce typical relational database constraints. Quite expensive."
"They don't have any SLAs in place. It would be better if they did."
"The cost of the solution could be reduced."
"Limitations in group by projections is where I would like to see an improvement."
"It needs integration with multiple clouds."
"When it is about to reach the maximum storage capacity, it becomes slow."
"The documentation of Vertica is an area with shortcomings where improvements are required."
"I think they need an easy client so that you can write queries easily, but it's not necessarily a weak point. I think some users would need them."
"I have found that coding support could be simplified."
"Vertica seems to scale well, except for one use case where you are on a multi-node cluster. For example, if you had a nine-node cluster, one node goes down, then the eight nodes don't scale, because the absence of the node is very apparent, which is a problem. If you have nine nodes or multiple nodes, the whole idea is that if one of those nodes goes down, then you should not see an impact on the system if you have enough capacity. Even though we have enough capacity, you can still see the impact of the one node going down."
"Support is an area where it could get better."
Snowflake is ranked 1st in Data Warehouse with 94 reviews while Vertica is ranked 4th in Data Warehouse with 83 reviews. Snowflake is rated 8.4, while Vertica is rated 8.2. 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 Vertica writes " A user-friendly tool that needs to improve its documentation part". Snowflake is most compared with BigQuery, Azure Data Factory, Teradata, AWS Lake Formation and Oracle Autonomous Data Warehouse, whereas Vertica is most compared with SQL Server, Amazon Redshift, Teradata, BigQuery and Oracle Exadata. See our Snowflake vs. Vertica report.
See our list of best Data Warehouse vendors and best Cloud Data Warehouse vendors.
We monitor all Data Warehouse reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.