A well-received community post I recently made (re-posted 14 times at the time of this blog post):
https://www.linkedin.com/posts/erikgfesser_databricks-snowflake-dbengines-activity-7150225307155755008-E_uS
Some of you probably already heard the news last week that PostgreSQL, a perennial favorite, won the DB-Engines database product of the year award for 2023. However, what hasn't been cited as frequently is that Databricks was the runner-up winner for 2023, besting Snowflake which won the prior two years. I'm especially pleased because I was the individual behind getting Databricks added to the DB-Engines ranking after reaching out to Paul Andlinger in April 2022, which you can read about at the links I've provided in the comments below. This all started because I had noticed at the time that Gartner had included Databricks in its rankings, and DBEngines had not, and I wanted this gap to be closed after having successfully worked with Databricks since 2018 (the most recent implementation of which is one of the world's largest). Now that Databricks has surpassed Hive, my expectation is that it will continue to rise in the ranking, keeping in mind that Databricks is *much* more than a database, built on an opensource foundation for dataengineering and datascience, unlike the aforementioned competitor.
DB-Engines announcement from January 2, 2024:
https://db-engines.com/en/blog_post/106
My post from April 2022:
https://www.linkedin.com/posts/erikgfesser_gartner-databricks-database-activity-6925028958199570432-t5bW
My open letter to db-engines:
https://www.erikgfesser.com/weblog/2022/04/open-letter-to-db-engines-database-ranking-databricks-added-april-may-2022-snowflake-amazon-athena.html
Strategic Data & AI Advisor / Lead Product Specialist at Databricks:
This and the placement of Databricks in the newest Gartner MQ are the best recognition of the hard work and dedication of Databricks Product and Engineering over the past few years as we have built the new Warehouse product Databricks SQL. The progress is amazing, but we are just getting started.
Thanks, Erik Gfesser, as an early supporter of Databricks, we appreciate your help in setting the record straight.
Data Engineering Team Lead at Cycling Product Manufacturer & Distributor:
I think it should be much higher...
Gfesser: [Data Engineering Team Lead] rankings are proprietary, but keep in mind that rankings can be filtered based on the database model / product type. For example, DB-Engines categorizes Databricks as multi-model that includes both relational DBMS and document store, with separate rankings of 11 and 3, respectively.