Milvus vs Weaviate vs Qdrant vs Chroma

A side-by-side look at scores, pricing and features — with RECATOOLS' ASEAN-aware verdict for each.

	Milvus Billion-scale open-source vector DB behind Zilliz Cloud Visit	Weaviate Open-source vector DB with hybrid search, now backed by $200M Visit	Qdrant Rust vector search engine built for filtering-heavy AI workloads Visit	Chroma Python-first embedded vector DB, now a metered Chroma Cloud Visit
RECATOOLS Score	8.3 / 10	8 / 10	8.7 / 10	7.5 / 10
Capability	9	8	9	7
Value for money	9	8	9	8
Ease of use	6	6	6	8
ASEAN readiness	7	7	6	6
API quality	8	9	9	8
Pricing	Open Source	Open Source	Open Source	Open Source
Free tier	—	—	—	—
Paid from	—	—	—	—
Has API	✓	✓	✓	✓
Open source	✓	✓	✓	✓
Free to use	✓	✓	✓	✓
Users	—	—	—	—
Founded	2019	2019	2021	2022
Maker	—	—	—	—
Verdict	Milvus is the vector database teams reach for once scale actually matters — GPU-accelerated indexes, distributed deployment, and a CNCF-graduated governance model back a claim of 10,000+ enterprise users and 100 million+...	Weaviate pairs vector similarity with BM25 keyword search in a single query object, and built-in vectorizer modules mean you're not always wiring your own embedding pipeline. G2 reviewers (30+, averaging around 4.6) call...	Qdrant's pitch is speed with filters attached — G2 reviewers give it a 9.3 for semantic search accuracy and 9.1 for ease of use in head-to-head comparisons, and metadata filtering (combining vector similarity with struct...	Chroma's whole appeal is friction: pip install, a few lines of Python, and you have a working retrieval pipeline — which is why it's become close to a default for LangChain and LlamaIndex tutorials and early-stage RAG pr...
	Full review →	Full review →	Full review →	Full review →

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Comparisons cover up to 4 tools. Scores are RECATOOLS editorial assessments; verify current pricing on each vendor's site.