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.
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| Original publisher | DEV.to (Top) |
| Canonical URL | https://dev.to/hsnmnr/three-ways-to-set-up-cdc-from-postgres-to-clickhouse-2fob |
| Publication time | Sat, 30 May 2026 17:36:08 +0000 |
| Retrieval time | 2026-05-30T17:59:43.108Z |
| Last seen | 2026-05-30T17:59:43.108Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | FnZSvH5CXPn5 |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
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| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
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.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at DEV.to (Top).
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