head to head · open source
Elasticsearch vs Qdrant
Elasticsearch has 77,926 GitHub stars, 26,071 forks, 6,059 open issues and last shipped today. Qdrant has 34,650 stars, 2,682 forks, 704 open issues and last shipped yesterday. Elasticsearch leads on adoption by 125% (77,926 vs 34,650 stars). Elasticsearch is written in Java under a custom or non-standard licence; Qdrant is written in Rust under Apache-2.0. Elasticsearch has attracted 33% as many forks as stars, Qdrant 8%. Elasticsearch was the more recently maintained of the two, and both are self-hostable with no licence fee.
Two open source projects, one decision. Both are free and self-hostable — the differences are community size, license terms, language stack and release pace.
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Side by side
| Elasticsearch | Qdrant | |
|---|---|---|
| GitHub stars | ★ 78K | ★ 35K |
| License | Custom / other | Apache-2.0 |
| Written in | Java | Rust |
| Last push | 2026-09-18 | 2026-09-17 |
| Forks | ⑂ 26K | ⑂ 2.7K |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Elasticsearch if
- You weight community size — 78K stars and counting
- You want the Custom / other license terms
- Your stack matches Java
- You value the larger contributor base for long-term maintenance
pick Qdrant if
- You want the Qdrant feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches Rust
- You evaluated both and Qdrant fits your workflow better
About Elasticsearch
Elasticsearch is a distributed search and analytics engine built in Java, designed for near real time search, scalability, and high performance data querying on production workloads. It serves as the core storage and indexing layer of Elastic’s open stack and supports full text, structured, and vector based search.
read the full Elasticsearch overview →
About Qdrant
Qdrant is a vector similarity search engine and database built in Rust, designed for production use in AI applications. It stores, manages, and retrieves high dimensional vectors alongside associated metadata (payloads), supporting fast nearest neighbor search with filtering. It solves the problem of efficiently performing semantic or neural based matching at scale—such as finding similar images, recommending content, or powering retrieval augmented generation (RAG)—by replacing slow or inflexible brute force or index based approaches with a purpose built engine optimized for vector operations.…
read the full Qdrant overview →
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Frequently asked questions
Is Elasticsearch or Qdrant more popular?
Elasticsearch has 77,926 GitHub stars and Qdrant has 34,650. Elasticsearch has the larger community by that measure.
Are Elasticsearch and Qdrant free?
Both are open source. Elasticsearch has no licence declared in this registry, and Qdrant is licensed under Apache-2.0. Both are free to self-host.
What is the difference between Elasticsearch and Qdrant?
Elasticsearch is written in Java and Qdrant in Rust. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, Elasticsearch or Qdrant?
Choose Elasticsearch if you want the larger community (77,926 stars) or its Custom / other licence terms. Choose Qdrant if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.