Great exit for the PeerDB team, congratulations. However Postgres has improved so much over the years that many users don't need to move their data out of Postgres to get great performance for analytical queries.

At Tablespace https://www.tablespace.io we've built a ColumnStore Index natively as a Postgres extension that enables users to execute analytical queries in Postgres 2X faster than Clickhouse Cloud without moving their data https://www.tablespace.io/blog/postgres-columnstore-index-vs...

For transparency I'm the CEO of Tablespace.

Thanks for posting this question! I previously worked at Citus for 8 years, where we tried to bring real-time analytical capabilities to Postgres. It was common to see POCs go sideways, and several customers (including CloudFlare and Heap) moved from Citus to an analytics-specialized database. For example, CloudFlare moved from Citus to ClickHouse. This was one of the inspirations for me to build a company (PeerDB) that brings specialized OLTP and OLAP databases together.

This is not to say that Postgres cannot support larger-scale analytical workloads, but it will take time. ClickHouse has taken 10 years of effort and development to get where it is now.

I would love to understand how tablespace performs at scale in production workloads. Are there any references that you could share. :)

Please don't copy-paste comments. It makes merging threads a pain.

Probably best not to do marketing on top of someone else's announcement too... https://x.com/mitchellh/status/1759626842817069290?t=57h-biZ...

Congrats on Tablespace! it's good to see innovation in that space and I always love to see ClickBench mentioned in the wild :) (I work for ClickHouse).

I'm curious to hear your take about the tradeoffs that the HTAP model introduces? any impact on ingest times or query throughput for example?