Pinecone vs Weaviate vs Qdrant vs LlamaCloud

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

	Pinecone Serverless vector database with pay-per-use pricing 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	LlamaCloud Managed document parsing and RAG indexing from LlamaIndex Visit
RECATOOLS Score	8.1 / 10	8 / 10	8.7 / 10	7 / 10
Capability	8	8	9	7
Value for money	7	8	9	6
Ease of use	8	6	6	7
ASEAN readiness	6	7	6	6
API quality	9	9	9	8
Pricing	Freemium	Open Source	Open Source	Freemium
Free tier	—	—	—	—
Paid from	—	—	—	—
Has API	✓	✓	✓	✓
Open source	✗	✓	✓	✗
Free to use	✓	✓	✓	✓
Users	—	—	—	—
Founded	2019	2019	2021	2024
Maker	—	—	—	—
Verdict	Pinecone remains the reference point for managed vector databases: serverless architecture that auto-scales without index-sizing decisions, sub-second queries at billions of vectors, and SDKs across Python, JS and Java t...	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...	LlamaCloud is the commercial layer on top of the open-source LlamaIndex framework: hosted document parsing through LlamaParse, structured extraction via LlamaExtract, and managed retrieval indexes, all reachable from the...
	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.