head to head · open source
Qdrant vs Activeloop
Qdrant has 34,694 GitHub stars, 2,685 forks, 704 open issues and last shipped yesterday. Activeloop has 9,241 stars, 722 forks, 66 open issues and last shipped 4 months ago. Qdrant leads on adoption by 275% (34,694 vs 9,241 stars). Qdrant is written in Rust under Apache-2.0; Activeloop is written in C++ under Apache-2.0. Qdrant has attracted 8% as many forks as stars, Activeloop 8%. Qdrant was the more recently maintained of the two, and both are self-hostable with no licence fee. The two share 1 topic tag (mlops), so they are genuine substitutes rather than adjacent tools.
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
| Qdrant | Activeloop | |
|---|---|---|
| GitHub stars | ★ 35K | ★ 9.2K |
| License | Apache-2.0 | Apache-2.0 |
| Written in | Rust | C++ |
| Last push | 2026-09-19 | 2026-05-21 |
| Forks | ⑂ 2.7K | ⑂ 722 |
| Self-hosting | Yes | Yes |
| Data ownership | Your server | Your server |
pick Qdrant if
- You weight community size — 35K stars and counting
- You want the Apache-2.0 license terms
- Your stack matches Rust
- You value the larger contributor base for long-term maintenance
pick Activeloop if
- You want the Activeloop feature set and don't need the biggest community
- You prefer the Apache-2.0 license terms
- Your stack matches C++
- You evaluated both and Activeloop fits your workflow better
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 →
About Activeloop
Activeloop Deep Lake is an open source database for AI data, written in C++ under Apache 2.0. It presents itself as a tensor database and AI data runtime for agents, combining serverless Postgres with a multimodal datalake for scalable retrieval and training. The project lives in the machine learning infrastructure ecosystem.
read the full Activeloop overview →
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Frequently asked questions
Is Qdrant or Activeloop more popular?
Qdrant has 34,694 GitHub stars and Activeloop has 9,241. Qdrant has the larger community by that measure.
Are Qdrant and Activeloop free?
Both are open source. Qdrant is licensed under Apache-2.0 and Activeloop under Apache-2.0. Neither carries a licence fee.
What is the difference between Qdrant and Activeloop?
Qdrant is written in Rust and Activeloop in C++. The practical differences are community size, licence terms, language stack and release cadence — all compared in the table above.
Which should I choose, Qdrant or Activeloop?
Choose Qdrant if you want the larger community (34,694 stars) or its Apache-2.0 licence terms. Choose Activeloop if its feature set, stack or Apache-2.0 licence fits better. Both are self-hostable.