head to head · open source
Elasticsearch vs Qdrant
Elasticsearch has 78,457 GitHub stars, 26,234 forks, 6,059 open issues and last shipped yesterday. Qdrant has 35,375 stars, 2,791 forks, 704 open issues and last shipped 2 days ago. Elasticsearch leads on adoption by 122% (78,457 vs 35,375 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 | 2026-11-02 | 2026-11-01 |
| Forks | ⑂ 26K | ⑂ 2.8K |
| 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 Elasticsearch is a distributed search and analytics engine, scalable data store and vector database optimized for speed and relevance on production scale workloads. Elasticsearch is the foundation of Elastic's open Stack platform. Search in near real time over massive datasets, perform vector searches, integrate with generative AI applications, and much more. Use cases enabled by Elasticsearch include: Augmented Generation (RAG)] search] Full text search Logs Metrics Application performance monitoring (APM) Security logs \... and more! To learn more about Elasticsearch's features and…
read the full Elasticsearch overview →
About Qdrant
Vector Search Engine for the next generation of AI applications Qdrant (read: quadrant ) is a vector similarity search engine and vector database. It provides a production ready service with a convenient API to store, search, and manage points—vectors with an additional payload. Qdrant is tailored for extended filtering support, making it useful for all sorts of neural network or semantic based matching, faceted search, and other applications. Qdrant is written in Rust 🦀, which makes it fast and reliable even under high load. See benchmarks. With Qdrant, embeddings or neural network encoders can be turned into…
read the full Qdrant overview →
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Frequently asked questions
Is Elasticsearch or Qdrant more popular?
Elasticsearch has 78,457 GitHub stars and Qdrant has 35,375. 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 (78,457 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.