Three Ways to Set Up CDC from Postgres to ClickHouse
The article discusses three methods to implement Change Data Capture (CDC) from Postgres to ClickHouse. It highlights the importance of keeping ClickHouse in sync with Postgres for efficient analytical querying. The author evaluates the pros and cons of each method based on practical experience in production environments.
- ▪CDC captures every insert, update, and delete in Postgres and forwards it to another system.
- ▪The article evaluates three common methods to integrate Postgres CDC into ClickHouse.
- ▪One method involves using Kafka and Debezium, while another utilizes ClickHouse's built-in MaterializedPostgreSQL engine.
Opening excerpt (first ~120 words) tap to expand
try { if(localStorage) { let currentUser = localStorage.getItem('current_user'); if (currentUser) { currentUser = JSON.parse(currentUser); if (currentUser.id === 247119) { document.getElementById('article-show-container').classList.add('current-user-is-article-author'); } } } } catch (e) { console.error(e); } Hassan Munir Posted on May 30 • Originally published at hassanmunir.me Three Ways to Set Up CDC from Postgres to ClickHouse #postgres #clickhouse #database #dataengineering You cannot run analytical queries on the same Postgres primary that serves your application without paying for it in CPU and connections. A read replica does not help: Postgres is row-oriented and built for OLTP, not for scanning tens of millions of rows for a GROUP BY.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
Discussion
0 commentsMore from DEV.to (Top)
