ClickHouse vs Postgres: Which MCP should you use?
ClickHouse
Columnar OLAP database for analytics
Postgres
The world's most advanced open-source relational DB
TL;DR
ClickHouse is a columnar OLAP engine built for scanning billions of rows in milliseconds. Postgres is row-oriented OLTP — great for transactions and point reads. For dashboards over huge event tables, ClickHouse is often 100× faster; for user/order data, Postgres is the right tool.
Pick ClickHouse
Pick ClickHouse when you scan billions of events for analytics, time-series, or product telemetry.
Pick Postgres
Pick Postgres when you serve an application's OLTP workload (users, orders, sessions).
Feature-by-feature comparison
| Feature | 🟡ClickHouse | 🐘Postgres | Winner |
|---|---|---|---|
| Storage layout | Columnar | Row-oriented | Tie |
| OLAP scan speed | Extreme (100x+ Postgres) | Adequate | A |
| OLTP / point updates | Weak (eventual merges) | Excellent | B |
| SQL compliance | Mostly, with extensions | Strict | B |
| Compression | 10-100x | Moderate | A |
| Joins | Functional, limited planner | Mature optimizer | B |
| Real-time inserts | Async merges, batch-friendly | Row-at-a-time OK | Tie |
| Ops complexity | Higher (ZooKeeper/Keeper) | Lower | B |
Storage layout
TieClickHouse
Columnar
Postgres
Row-oriented
OLAP scan speed
AClickHouse
Extreme (100x+ Postgres)
Postgres
Adequate
OLTP / point updates
BClickHouse
Weak (eventual merges)
Postgres
Excellent
SQL compliance
BClickHouse
Mostly, with extensions
Postgres
Strict
Compression
AClickHouse
10-100x
Postgres
Moderate
Joins
BClickHouse
Functional, limited planner
Postgres
Mature optimizer
Real-time inserts
TieClickHouse
Async merges, batch-friendly
Postgres
Row-at-a-time OK
Ops complexity
BClickHouse
Higher (ZooKeeper/Keeper)
Postgres
Lower
Best for
ClickHouse
- OLAP scan speed: Extreme (100x+ Postgres)
- Compression: 10-100x
Best for
Postgres
- OLTP / point updates: Excellent
- SQL compliance: Strict
- Joins: Mature optimizer
- Ops complexity: Lower
Migration path
Don't migrate — run both. Use Postgres for OLTP, replicate to ClickHouse for analytics via Debezium→Kafka→clickhouse-kafka-connect or PeerDB. If you must move a workload: re-model tables around queries (denormalize, pick MergeTree ORDER BY matching filters), accept that UPDATE/DELETE are heavy in ClickHouse.
Frequently asked questions
What is the main difference between ClickHouse and Postgres?
ClickHouse is a columnar OLAP engine built for scanning billions of rows in milliseconds. Postgres is row-oriented OLTP — great for transactions and point reads. For dashboards over huge event tables, ClickHouse is often 100× faster; for user/order data, Postgres is the right tool. In short: ClickHouse — Columnar OLAP database for analytics. Postgres — The world's most advanced open-source relational DB.
When should I pick ClickHouse over Postgres?
Pick ClickHouse when you scan billions of events for analytics, time-series, or product telemetry.
When should I pick Postgres over ClickHouse?
Pick Postgres when you serve an application's OLTP workload (users, orders, sessions).
Can I migrate from one to the other?
Don't migrate — run both. Use Postgres for OLTP, replicate to ClickHouse for analytics via Debezium→Kafka→clickhouse-kafka-connect or PeerDB. If you must move a workload: re-model tables around queries (denormalize, pick MergeTree ORDER BY matching filters), accept that UPDATE/DELETE are heavy in ClickHouse.
Do ClickHouse and Postgres both work with MCP-compatible AI agents?
Yes. Both have MCP servers installable via MCPizy (mcpizy install clickhouse and mcpizy install postgres). They work identically across Claude Code, Claude Desktop, Cursor, Windsurf, and any other MCP-compatible client. You can install both side by side and route queries in your agent's prompt.
More Database comparisons
Supabase vs Postgres
Supabase is managed Postgres plus auth, storage, edge functions, and realtime. Plain Postgres gives you the same battle-tested engine without the batteries — you run it yourself. Supabase wins for speed-to-product; Postgres wins for full control and cost at scale.
Supabase vs Firebase
Both are BaaS offerings. Supabase is Postgres-based (relational, SQL, open-source), Firebase is Firestore-based (NoSQL, proprietary, Google Cloud). Supabase wins if you want SQL, lower lock-in, and predictable pricing. Firebase wins for mobile-first apps tied to Google's ecosystem.
Postgres vs MySQL
Both are mature open-source relational databases. Postgres has richer SQL (CTEs, window functions, JSON, arrays, extensions), stricter standards compliance, and better for complex analytics. MySQL is simpler, often faster on basic read-heavy workloads, and dominates WordPress/PHP ecosystems.
Install both with MCPizy
Not sure? Run both side by side — swap between them in your AI agent with a single config line.