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

⭐ 77,597

⭐ 28,474

Contributors

👥 2,516

👥 1,476

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

81/100 (stable)

70/100 (stable)

Community Health

95/100 (excellent)

81/100 (good)

Maturity Index

93/100 (mature)

71/100 (established)

Innovation Score

64/100 (progressive)

58/100 (progressive)

Risk Score (higher is safer)

86/100 (minimal)

75/100 (minimal)

Developer Experience

53/100 (needs-improvement)

Links

🌐 Visit Website View on GitHub

Elasticsearch Strengths

✓ More popular (77,597 stars)
✓ Larger community (2,516 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

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Data source: GitHub API

Last updated: 7/28/2026