head to head · open source

DBeaver vs Qdrant

DBeaver has 51,791 GitHub stars, 4,371 forks, 3,334 open issues and last shipped yesterday. Qdrant has 34,638 stars, 2,680 forks, 704 open issues and last shipped yesterday. DBeaver leads on adoption by 50% (51,791 vs 34,638 stars). DBeaver is written in Java under Apache-2.0; Qdrant is written in Rust under Apache-2.0. DBeaver has attracted 8% as many forks as stars, Qdrant 8%. DBeaver 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.

DBeaver ★ 52K Qdrant ★ 35K category Infrastructure & Operations

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Side by side

DBeaver Qdrant
GitHub stars ★ 52K ★ 35K
License Apache-2.0 Apache-2.0
Written in Java Rust
Last push 2026-09-17 2026-09-17
Forks ⑂ 4.4K ⑂ 2.7K
Self-hosting Yes Yes
Data ownership Your server Your server

pick DBeaver if

  • You weight community size — 52K stars and counting
  • You want the Apache-2.0 license terms
  • Your stack matches Java
  • You value the larger contributor base for long-term maintenance

full DBeaver profile →

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

full Qdrant profile →

About DBeaver

DBeaver is a free, multi platform database management tool built in Java, designed for developers, SQL programmers, database administrators, and analysts. It operates across Windows, macOS, and Linux and integrates with the Eclipse based plugin ecosystem via OSGi and Eclipse RCP frameworks.

read the full DBeaver 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 →

More in Infrastructure & Operations

Immich ★ 114K Uptime Kuma ★ 91K worldmonitor ★ 87K mall ★ 85K NetData ★ 81K Elasticsearch ★ 78K

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More Databases projects

Compare either of these against the rest of the Databases field.

DBeaver vs mall DBeaver vs Prometheus DBeaver vs NocoDB DBeaver vs etcd DBeaver vs orm DBeaver vs Milvus DBeaver vs TiDB DBeaver vs drawDB DBeaver vs typeorm DBeaver vs AnotherRedisDesktopManager DBeaver vs rocksdb DBeaver vs InfluxDB

Frequently asked questions

Is DBeaver or Qdrant more popular?

DBeaver has 51,791 GitHub stars and Qdrant has 34,638. DBeaver has the larger community by that measure.

Are DBeaver and Qdrant free?

Both are open source. DBeaver is licensed under Apache-2.0 and Qdrant under Apache-2.0. Neither carries a licence fee.

What is the difference between DBeaver and Qdrant?

DBeaver 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, DBeaver or Qdrant?

Choose DBeaver if you want the larger community (51,791 stars) or its Apache-2.0 licence terms. Choose Qdrant if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.