We performed a comparison between Dremio and VMware Tanzu Greenplum 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."
"Everyone uses Dremio in my company; some use it only for the analytics function."
"We primarily use Dremio to create a data framework and a data queue."
"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."
"Dremio gives you the ability to create services which do not require additional resources and sterilization."
"It's one of the fastest databases in the market. It's easy to use. From a maintenance perspective it's a good product. The segmentation, or architecture of the product is different than other databases such as Oracle. So even in 10 years, the data distribution for such segments will not affect other segments. The query performance of the product, for complex queries, is very good. It has good integration with Hadoop."
"It works very well with large database queries."
"The parallel load features mean that Greenplum is capable of high-volume data loading in parallel to all of the cluster segments, which is really valuable."
"Scalability is simple because it's an MPP database. If you need more processing power or you need more storage, you just add a few more nodes in the cluster. It works on common commodity hardware. You can use any type of server. You don't need to have proprietary hardware. It's fairly flexible."
"A very good, open-source platform."
"Tanzu Greenplum's most valuable features include the integration of modern data science approaches across an MPP platform."
"Helps us to achieve large-scale analytics."
"Pivotal Greenplum's shared-nothing architecture."
"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."
"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."
"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."
"I cannot use the recursive common table expression (CTE) in Dremio because the support page says it's currently unsupported."
"It shows errors sometimes."
"Lacks sufficient inbuilt machine-learning functions for complex use cases."
"They should add more analytics. Their documentation could also be improved so that I don't have to bother my co-workers and tech support so often."
"The initial setup is somewhat complex and the out-of-the-box configuration requires optimization."
"We would like to see Greenplum maintain a closer relationship with and parity to features implemented in PostgreSQL."
"One of the disadvantages, not a disadvantage with the product itself, but overall, is the expertise in the marketplace. It's not easy to find a Greenplum administrator in the market, compared to other products such as Oracle."
"Extra filters would be helpful."
"Initial setup is a little complex. It took around two weeks to deploy."
"Some integration with other platforms like design tools, and ETL development tools, that will enable some advanced functionality, like fully down processing, etc."
Dremio is ranked 11th in Cloud Data Warehouse with 6 reviews while VMware Tanzu Greenplum is ranked 9th in Data Warehouse with 36 reviews. Dremio is rated 8.6, while VMware Tanzu Greenplum is rated 7.8. 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 VMware Tanzu Greenplum writes "Very efficient at large scale analytics; lacks inbuilt machine-learning functions for complex use cases". Dremio is most compared with Databricks, Snowflake, Starburst Enterprise, Amazon Redshift and Microsoft Azure Synapse Analytics, whereas VMware Tanzu Greenplum is most compared with Oracle Exadata, Vertica, Oracle Database Appliance, Apache Hadoop and Snowflake. See our Dremio vs. VMware Tanzu Greenplum report.
See our list of best Cloud Data Warehouse vendors.
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