We performed a comparison between Dremio and Vertica based on real PeerSpot user reviews.
Find out in this report how the two Cloud Data Warehouse solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."Dremio allows querying the files I have on my block storage or object storage."
"The most valuable feature of Dremio is it can sit on top of any other data storage, such as Amazon S3, Azure Data Factory, SGFS, or Hive. The memory competition is good. If you are running any kind of materialized view, you'd be running in memory."
"We primarily use Dremio to create a data framework and a data queue."
"Dremio gives you the ability to create services which do not require additional resources and sterilization."
"Dremio enables you to manage changes more effectively than any other data warehouse platform. There are two things that come into play. One is data lineage. If you are looking at data in Dremio, you may want to know the source and what happened to it along the way or how it may have been transformed in the data pipeline to get to the point where you're consuming it."
"Everyone uses Dremio in my company; some use it only for the analytics function."
"Any novice user can tune vertical queries with minimal training (or no training at all)."
"The hardware usage and speed has been the most valuable feature of this solution. It is very fast and has saved us a lot of money."
"Vertica's most outstanding features are the compression rates achieved and the speed of access of high volume data."
"Vertica is easy to use and provides really high performance, stability, and scalability."
"Vertica has a few features that I like. From an architecture standpoint, they have separated compute and storage. So you have low-cost object storage for primary storage and the ability to have several sub-clusters working off the same ObjectStore. So it provides workload isolation."
"Eighty percent of the ETL operations have improved since implementing this solution."
"The extensibility and efficiency provided by their C++ SDK."
"The fast columnar store database structure allows our query times to be at least 10x faster than on any other database."
"It shows errors sometimes."
"Dremio takes a long time to execute large queries or the executing of correlated queries or nested queries. Additionally, the solution could improve if we could read data from the streaming pipelines or if it allowed us to create the ETL pipeline directly on top of it, similar to Snowflake."
"We've faced a challenge with integrating Dremio and Databricks, specifically regarding authentication. It is not shaking hands very easily."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"They have an automated tool for building SQL queries, so you don't need to know SQL. That interface works, but it could be more efficient in terms of the SQL generated from those things. It's going through some growing pains. There is so much value in tools like these for people with no SQL experience. Over time, Dermio will make these capabilities more accessible to users who aren't database people."
"Dremio doesn't support the Delta connector. Dremio writes the IT support for Delta, but the support isn't great. There is definitely room for improvement."
"We are looking for a cheaper deployment for the solution. Although we did a lot of benchmarks, like Redshift. We tried Redshift, it didn't work. It didn't work out for us as well."
"Promotion/marketing must be improved, even though it is a very useful product at very good price, it is not as "popular" as it should be."
"Limitations in group by projections is where I would like to see an improvement."
"Whatever's out, the core is not always as great as the engine, especially their first version."
"Some of our small to medium-sized customers would like to see containerization and flexibility from the deployment standpoint."
"Documentation has become much better, but can always use some improvement."
"Suboptimal projection design causes queries to not scale linearly."
"Fact-to-fact joins on multi-billion record tables perform poorly."
Dremio is ranked 11th in Cloud Data Warehouse with 6 reviews while Vertica is ranked 7th in Cloud Data Warehouse with 83 reviews. Dremio is rated 8.6, while Vertica is rated 8.2. The top reviewer of Dremio writes "It enables you to manage changes more effectively than any other platform". On the other hand, the top reviewer of Vertica writes " A user-friendly tool that needs to improve its documentation part". Dremio is most compared with Databricks, Snowflake, Starburst Enterprise, Amazon Redshift and Amazon QuickSight, whereas Vertica is most compared with Snowflake, SQL Server, Amazon Redshift, Teradata and Oracle Exadata. See our Dremio vs. Vertica report.
See our list of best Cloud Data Warehouse vendors.
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