Elasticsearch vs MongoDB: Key Differences & When to Use Each

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

Key Differences

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

Feature

Elasticsearch

Database

MongoDB

Database

Side-by-side comparison of developer tools
Distributed RESTful search and analytics engine
NoSQL document database
GitHub Stars
⭐ 76,630
⭐ 28,286
Contributors
👥 2,471
👥 1,431
Pricing
✓ Free
Enterprise: Contact sales
✓ Free
Enterprise: Contact sales
Languages
Java
C++
Features
  • • Elasticsearch
  • • Java
  • • Search Engine
  • • C Plus Plus
  • • Database
  • • Mongodb
  • • Nosql
Integrations
  • • elasticsearch
  • • mongodb
Momentum Score
66/100 (stable)
66/100 (stable)
Community Health
95/100 (excellent)
81/100 (good)
Maturity Index
93/100 (mature)
71/100 (established)
Innovation Score
65/100 (progressive)
59/100 (progressive)
Risk Score (higher is safer)
87/100 (minimal)
76/100 (minimal)
Developer Experience
54/100 (needs-improvement)
54/100 (needs-improvement)
Links
🌐 Visit Website View on GitHub
🌐 Visit Website View on GitHub

Elasticsearch Strengths

  • ✓ More popular (76,630 stars)
  • ✓ Larger community (2,471 contributors)

MongoDB Strengths

  • ✓ More features (4 listed)

When to Use Elasticsearch vs MongoDB

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

Related comparisons

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

More Comparisons

View Elasticsearch → View MongoDB → Search More Tools →

Data source: GitHub API

Last updated: 5/4/2026