cloudberry

Gradually transforming Cloudberry Database into a data foundation supporting AI/ML applications, based on Directory Table, pgvector, and PostgresML.

Different dev team too, afaik none of the original Greenplum team was involved with Cloudberry until very recently.

Join the growing community of Cloudberry users who are transforming their data strategies and driving success in their businesses.

Delighted to see Greenplum mentioned in this article, also equally pleased to see Apache Cloudberry mentioned in the comments.

It's not super automatic but CloudBerry Explorer for Azure [1] is free and has a pretty good folder sync feature.

This is mostly correct, but it's worth mentioning that cloudberry substantially predates Greenplum going closed source.

The Challenge Harvest Analytics relied heavily on a lakehouse architecture, using kafka_fdw to pull streaming data into their Apache Cloudberry database.

Automatic SQL Rewriting: When team members queried external data, Cloudberry automatically recognized SQL and rewrote it to utilize the Dynamic Tables.

The Cloudberry Database is just one alternative and option for the existing Greenplum users if they want to continue using it.

In what way would you say Cloudberry lags behind Greenplum technology-wise?

Like ClickHouse, Cloudberry supports columnar table layouts (like CH's MergeTree engine family) as well as the native Postgres row-oriented layout (like CH's Atomic table engine).

Kind of like CloudBerry Explorer but for more than S3.

In the Cloudberry architecture, as with Greenplum, database tables are partitioned into "segments", which are automatically distributed over a cluster of "segment hosts".

I can't compare CH's optimizer to Cloudberry's, but I suspect the latter is more sophisticated.

The team could continue using their familiar tools while benefiting from the advanced capabilities of Cloudberry.

Cloudberry is not so bad compared to some; they are now up to date with Postgres 14, I believe.