ClickHouse vs Elasticsearch: Key Differences & When to Use Each

Comprehensive side-by-side comparison of features, pricing, and metrics

Key Differences

Compare ClickHouse and Elasticsearch across features, pricing, integrations, and community metrics. ClickHouse / Elasticsearch.

Feature

ClickHouse

Database

Elasticsearch

Database

Side-by-side comparison of developer tools
Column-oriented database for OLAP
Distributed RESTful search and analytics engine
GitHub Stars
⭐ 47,194
⭐ 76,630
Contributors
👥 2,844
👥 2,471
Pricing
✓ Free
Enterprise: Contact sales
✓ Free
Enterprise: Contact sales
Languages
C++
Java
Features
  • • Ai
  • • Analytics
  • • Big Data
  • • Clickhouse
  • • Cloud Native
  • • Elasticsearch
  • • Java
  • • Search Engine
Integrations
No integrations listed
  • • elasticsearch
Momentum Score
95/100 (slowing)
66/100 (stable)
Community Health
77/100 (good)
95/100 (excellent)
Maturity Index
85/100 (mature)
93/100 (mature)
Innovation Score
83/100 (innovative)
65/100 (progressive)
Risk Score (higher is safer)
94/100 (minimal)
87/100 (minimal)
Developer Experience
95/100 (excellent)
54/100 (needs-improvement)
Links
🌐 Visit Website View on GitHub
🌐 Visit Website View on GitHub

ClickHouse Strengths

  • ✓ Larger community (2,844 contributors)
  • ✓ More features (5 listed)

Elasticsearch Strengths

  • ✓ More popular (76,630 stars)

When to Use ClickHouse vs Elasticsearch

Use ClickHouse when its strengths align better with your stack and team needs, and choose Elasticsearch when its ecosystem, integrations, or cost profile is a better fit.

Related comparisons

ClickHouse vs Redis → Elasticsearch vs Redis → ClickHouse vs TiDB → Elasticsearch vs TiDB → ClickHouse vs CockroachDB → Elasticsearch vs CockroachDB → ClickHouse vs InfluxDB → Elasticsearch vs InfluxDB → ClickHouse vs MongoDB → Elasticsearch vs MongoDB → ClickHouse vs TimescaleDB → Elasticsearch vs TimescaleDB →

More Comparisons

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Data source: GitHub API

Last updated: 5/4/2026