TabbyML vs Zilliz

TabbyML and Zilliz (Vector Database for Enterprise-grade AI and LLM applications) both appear on the Smoower Developer Ecosystem Index.

Zilliz (rank #122) holds a modest lead over TabbyML (rank #569) on the overall Smoower ecosystem score (54 vs 35). The gap of 19 points reflects composite signals across code, docs, community and reach.

On code quality (the state of repositories, tests, releases and polish), Zilliz is clearly ahead of TabbyML. On education (docs, guides and learning material for developers), Zilliz is clearly ahead of TabbyML. On community (issue response, PR reviews and discussion health), Zilliz is slightly ahead of TabbyML. On reach (how visible the ecosystem is beyond its own repos), TabbyML is ahead of Zilliz. On momentum (release cadence and how fast the ecosystem moves), Zilliz is clearly ahead of TabbyML.

TabbyML carries 34,010 GitHub stars across 18 public repos, with 5 repositories active in the last 90 days and 12 external contributors on record. Zilliz shows 37,860 stars across 71 public repos, 29 active in the last 90 days and 105 external contributors.

TabbyML is the stronger read for anyone weighting reach. Zilliz looks better where momentum is the deciding factor. The table below breaks the scores down pillar by pillar; the linked profiles cover the underlying repos, docs and community signals in full.