# Postgres to ClickHouse: Data Modeling Tips V2

DevFeed: [Postgres to ClickHouse: Data Modeling Tips V2](<https://devfeed.tech/articles/postgres-to-clickhouse-data-modeling-tips-v2-5521.md>)

Original publisher: [Read original article](<https://clickhouse.com/blog/postgres-to-clickhouse-data-modeling-tips-v2>)

Author: Lionel Palacin & Sai Srirampur

Published: 2025-03-06T00:00:00Z

Content type: article

Language: en

Sources: [ClickHouse Blog](<https://devfeed.tech/sources/clickhouse-blog.md>)

Topics: [clickhouse](<https://devfeed.tech/topics/clickhouse.md>), [data-modeling](<https://devfeed.tech/topics/data-modeling.md>), [PostgreSQL](<https://devfeed.tech/topics/postgresql.md>), [Replication](<https://devfeed.tech/topics/replication.md>), [Databases](<https://devfeed.tech/topics/databases.md>), [Stack Overflow](<https://devfeed.tech/topics/stackoverflow.md>), [Python](<https://devfeed.tech/topics/python.md>)

Tags: [best-practices](<https://devfeed.tech/tags/best-practices.md>), [blog-post](<https://devfeed.tech/tags/blog-post.md>), [clickhouse](<https://devfeed.tech/tags/clickhouse.md>), [data-modeling](<https://devfeed.tech/tags/data-modeling.md>), [deep-dive](<https://devfeed.tech/tags/deep-dive.md>), [github](<https://devfeed.tech/tags/github.md>), [how-to](<https://devfeed.tech/tags/how-to.md>), [learn](<https://devfeed.tech/tags/learn.md>), [performance](<https://devfeed.tech/tags/performance.md>), [postgres](<https://devfeed.tech/tags/postgres.md>), [python](<https://devfeed.tech/tags/python.md>), [replication](<https://devfeed.tech/tags/replication.md>)

## AI overview

This advanced article explains how to replicate PostgreSQL data into ClickHouse for real-time analytics using CDC, ClickPipes, or PeerDB. It covers data modeling and query-performance practices, including deduplication, ordering keys, JOIN optimization, materialized views, and denormalization, with examples based on a StackOverflow dataset.

## Source excerpt

Dive into how Postgres-to-ClickHouse replication works, and learn best practices for data deduplication, custom ordering keys, optimizing JOINs, denormalization, and more.