Zvec

license

Apache-2.0(OSI)

source

public

core features withheld

no

Apache-2.0 license body confirmed. The repository is public and unarchived and builds the whole product, and the README describes no paid tier, enterprise edition or license-gated build beside it, so source is public and the core ungated.

• https://pypi.org/pypi/zvec/json recorded 2026-09-30

  PyPI metadata lists "License :: OSI Approved :: Apache Software License" as a classifier for zvec.

• https://raw.githubusercontent.com/alibaba/zvec/main/LICENSE recorded 2026-09-30

  LICENSE file is the Apache-2.0 text: "Apache License" and "Version 2.0, January 2004" and "TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION".

• https://raw.githubusercontent.com/alibaba/zvec/main/README.md recorded 2026-09-30

  README calls Zvec "an open-source, in-process vector database" and shows the Apache 2.0 license badge; searched the body for enterprise, paid tier and license key: none.

Zvec's adoption reading is based on PyPI downloads of the `zvec` package rather than its GitHub stars, since downloads measure use directly while stars measure attention, and the two point in different directions here. As an in-process library with no separate server, the package is the product itself, so its download count is a direct read of use.

• https://pypistats.org/api/packages/zvec/recent recorded 2026-08-18

  last_month downloads = 40,993 for zvec

Zvec offers real index breadth (flat, HNSW, HNSW-RaBitQ, IVF and sparse) plus native full-text and hybrid search, embedded directly in the application process. It has no server or cluster of its own, so it covers much less of the persist-index-retrieve path than Vespa does.

• https://raw.githubusercontent.com/alibaba/zvec/main/README.md recorded 2026-09-30

  README describes an in-process library ("Pure local, no servers, no config, no fuss.") that will "Support dense and sparse embeddings, multi-vector queries" and offers "Native keyword-based full-text search" and "Multiple processes can read the same collection simultaneously; writes are single-process exclusive."

• https://raw.githubusercontent.com/alibaba/zvec/main/README.md recorded 2026-09-30

  README lists "Fuse vector similarity, full-text search, and structured filters in a single query for precise results." as hybrid search.

• https://zvec.org/en/docs/db/concepts/fts-index/ recorded 2026-09-30

  Full-text index page says the index "supports natural language queries, phrase matching, and boolean expressions, ranked by BM25 relevance scoring."

• https://zvec.org/en/docs/db/concepts/vector-index/ recorded 2026-09-30

  Vector index page says "Zvec supports the following vector index types, each suited to different use cases, dataset sizes, and performance requirements:" and lists HNSW-RaBitQ.