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# ClickHouse vs PostgreSQL: Choosing the Right Database for Analytics

**[BigData Boutique blog](https://daily.dev/sources/bigdataboutique)** · 10 min read · 3 upvotes · 0 comments

## Summary

PostgreSQL and ClickHouse serve different purposes: PostgreSQL excels at transactional workloads with row-oriented storage, while ClickHouse's columnar architecture dominates large-scale analytics. For datasets under 50K rows, PostgreSQL read replicas work fine, but beyond millions of rows, ClickHouse delivers 10x-1000x faster queries through columnar compression (10x-30x ratios), vectorized execution, and specialized table engines. The recommended production pattern is PostgreSQL for OLTP plus ClickHouse for analytics, connected via CDC, allowing each database to operate in its sweet spot while reducing storage costs and operational complexity.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://bigdataboutique.com/blog/clickhouse-vs-postgresql>

## Similar posts on daily.dev

- [Postgres vs ClickHouse is the wrong question. I use both.](https://daily.dev/posts/postgres-vs-clickhouse-is-the-wrong-question-i-use-both--kj77irn0i) · Medium · 0 upvotes · 0 comments

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Tags: [#database](https://daily.dev/tags/database), [#postgresql](https://daily.dev/tags/postgresql), [#data-engineering](https://daily.dev/tags/data-engineering), [#clickhouse](https://daily.dev/tags/clickhouse), [#olap](https://daily.dev/tags/olap)

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