Very interesting take — I see where you’re coming from. Yes, there are caveats and differences between ClickHouse and Postgres. Much of this stems from the nature of the workloads they are built for: Postgres for OLTP and ClickHouse for OLAP.
From what we’ve observed, the learning curve typically ranges from a few weeks for smaller to medium migrations to 1–2 months for larger ones moving real-time OLAP workloads from Postgres to ClickHouse. Still, customers are making the switch and finding value — hundreds (or more) are using both technologies together to scale their real-time applications: Postgres for low-latency, high-throughput transactions and ClickHouse for blazing-fast (100x faster) analytics.
We’re actively working to bridge the gap between the two systems, with features like faster UPDATEs, enhanced JOINs and more. That’s why I’m not sure your comment is fully generalizable — the differences largely stem from the distinct workloads they support, and we’re making steady progress in narrowing that gap.
Great question, exactly CDC from Postgres to ClickHouse and adapting the application to start using ClickHouse for analytics. Through the PeerDB acquisition, ClickHouse now has native CDC capabilities that work at any scale (few 10s of GB to 10s of TB Postgres databases). You can use ClickPipes if you’re on ClickHouse Cloud, or PeerDB if you’re using ClickHouse OSS.
We’ve been doing our best to address and clarify these differences, whether through product features like this one or by publishing content to educate users. For example: https://clickhouse.com/blog/postgres-to-clickhouse-data-mode... https://www.youtube.com/watch?v=9ipwqfuBEbc.
From what we’ve observed, the learning curve typically ranges from a few weeks for smaller to medium migrations to 1–2 months for larger ones moving real-time OLAP workloads from Postgres to ClickHouse. Still, customers are making the switch and finding value — hundreds (or more) are using both technologies together to scale their real-time applications: Postgres for low-latency, high-throughput transactions and ClickHouse for blazing-fast (100x faster) analytics.
We’re actively working to bridge the gap between the two systems, with features like faster UPDATEs, enhanced JOINs and more. That’s why I’m not sure your comment is fully generalizable — the differences largely stem from the distinct workloads they support, and we’re making steady progress in narrowing that gap.
- Sai from the ClickHouse team here.