Creating advanced vector search technology
Vector Database for Enterprise-grade AI and LLM applications
Qdrant vs Zilliz
Developer ecosystem comparison across GitHub activity, SDKs, documentation, community, reach and momentum.
Qdrant (Creating advanced vector search technology) and Zilliz (Vector Database for Enterprise-grade AI and LLM applications) both appear on the Smoower Developer Ecosystem Index.
Qdrant (rank #5) holds a modest lead over Zilliz (rank #115) on the overall Smoower ecosystem score (74 vs 57). The gap of 17 points reflects composite signals across code, docs, community and reach.
On code quality (the state of repositories, tests, releases and polish), Qdrant is slightly ahead of Zilliz. On education (docs, guides and learning material for developers), Qdrant is slightly ahead of Zilliz. On community (issue response, PR reviews and discussion health), Qdrant is ahead of Zilliz. On reach (how visible the ecosystem is beyond its own repos), Qdrant is slightly ahead of Zilliz. On momentum (release cadence and how fast the ecosystem moves), Qdrant is clearly ahead of Zilliz.
Qdrant carries 45,822 GitHub stars across 132 public repos, with 89 repositories active in the last 90 days and 122 external contributors on record. Zilliz shows 38,722 stars across 74 public repos, 30 active in the last 90 days and 99 external contributors.
Qdrant is the stronger read for anyone weighting momentum. Zilliz makes more sense for teams already using its adjacent tools. The table below breaks the scores down pillar by pillar; the linked profiles cover the underlying repos, docs and community signals in full.
Side-by-side metrics
| Metric | Qdrant | Zilliz |
|---|---|---|
| Ranking | ||
| Overall rank | #5 | #115 |
| Pillars | ||
| Overall | 74 | 57 |
| Code | 70 | 67 |
| Education | 88 | 84 |
| Community | 64 | 49 |
| Reach | 70 | 62 |
| Momentum | 66 | 39 |
| Builder experience | 0 | 0 |
| Signals | ||
| Stars | 45,822 | 38,722 |
| Forks | 4,571 | 4,103 |
| Public repos | 132 | 74 |
| Active repos (90d) | 89 | 30 |
| External contributors | 122 | 99 |
| Avg polish | 70 | 64 |
| Avg AI-readiness | 49 | 62 |