# Postgres + ClickHouse Architectural Patterns

DevFeed: [Postgres + ClickHouse Architectural Patterns](<https://devfeed.tech/articles/postgres-clickhouse-architectural-patterns-19116.md>)

Original publisher: [Read original article](<https://severalnines.com/blog/postgres-clickhouse-architectural-patterns/>)

Author: Agus Syafaat

Published: 2026-08-26T08:08:43Z

Content type: article

Language: en

Sources: [SeveralNines](<https://devfeed.tech/sources/severalnines.md>)

Topics: [clickhouse](<https://devfeed.tech/topics/clickhouse.md>), [PostgreSQL](<https://devfeed.tech/topics/postgresql.md>), [Databases](<https://devfeed.tech/topics/databases.md>), [Architecture & Design](<https://devfeed.tech/topics/architecture-design.md>), [data-platforms](<https://devfeed.tech/topics/data-platforms.md>), [real-time](<https://devfeed.tech/topics/real-time.md>), [Transactions](<https://devfeed.tech/topics/transactions.md>), [Low Latency](<https://devfeed.tech/topics/low-latency.md>), [dashboards](<https://devfeed.tech/topics/dashboards.md>)

Tags: [analytics](<https://devfeed.tech/tags/analytics.md>), [architecture](<https://devfeed.tech/tags/architecture.md>), [clickhouse](<https://devfeed.tech/tags/clickhouse.md>), [clustercontrol](<https://devfeed.tech/tags/clustercontrol.md>), [database-general](<https://devfeed.tech/tags/database-general.md>), [hybrid-operations](<https://devfeed.tech/tags/hybrid-operations.md>), [latency](<https://devfeed.tech/tags/latency.md>), [olap](<https://devfeed.tech/tags/olap.md>), [postgres](<https://devfeed.tech/tags/postgres.md>), [postgresql](<https://devfeed.tech/tags/postgresql.md>), [real-time](<https://devfeed.tech/tags/real-time.md>), [time](<https://devfeed.tech/tags/time.md>), [transactions](<https://devfeed.tech/tags/transactions.md>)

## AI overview

This article explains architectural patterns that combine PostgreSQL and ClickHouse. PostgreSQL serves as the authoritative transactional system for OLTP workloads, while ClickHouse handles large-scale analytical queries and real-time analytics. Continuous Change Data Capture synchronization connects the systems and separates transactional and analytical workloads.

## Source excerpt

The role of databases has shifted significantly as modern applications must deliver real-time analytics, dashboards, and machine learning alongside low-latency transaction processing. Handling these diverse demands with a single relational database has become unsustainable under growing data volumes. Consequently, organizations are adopting specialized database architectures where multiple engines work together based on their strengths, allowing [...] The post Postgres + ClickHouse Architectural Patterns appeared first on Severalnines.