Understanding Postgres-to-ClickHouse Integration for Transactional Workloads and Analytics
By
saisrirampur
10mo ago· 17 min readenNews
100/100
Golden Brown
Bagelometer↗
Toasted golden, schmeared with insight. Top of the rack.
Score100TypenewsSentimentneutral
Summary
The article discusses the integration of Postgres and ClickHouse for transactional workloads and analytics, focusing on Change Data Capture (CDC) as a common approach. It explores implementing Postgres CDC to ClickHouse using tools like PeerDB and provides best practices for data deduplication, custom ordering keys, optimizing JOINs, and denormalization.
Key quotes
· 4 pulledEach is a purpose-built database optimized for its respective workload.
CDC continuously tracks inserts, updates, and deletes in Postgres and replicates them to ClickHouse, enabling real-time analytics.
You can implement Postgres CDC to ClickHouse using PeerDB, an open-source replication tool, or leverage a fully integrated experience in
Dive into how Postgres-to-ClickHouse replication works, and learn best practices for data deduplication, custom ordering keys, optimizing JOINs, denormalization, and more.
Dive into how Postgres-to-ClickHouse replication works, and learn best practices for data deduplication, custom ordering keys, optimizing JOINs, denormalization, and more.
