Qdrant vs Weaviate
A side-by-side look at scores, pricing and features — with RECATOOLS' ASEAN-aware verdict for each.
Qdrant
Rust vector search engine built for filtering-heavy AI workloads
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Weaviate
Open-source vector database with hybrid search built in
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| RECATOOLS Score | 8.7 / 10 | 8 / 10 |
| Capability | ||
| Value for money | ||
| Ease of use | ||
| ASEAN readiness | ||
| API quality | ||
| Pricing | Open Source | Open Source |
| Free tier | Free forever cluster: 1 node, 0.5 vCPU, 1GB RAM, 4GB disk (~1M 768-dim vectors per docs), no card; suspended after 1 week idle. Self-hosted engine free (Apache-2.0) | Always-free Weaviate Cloud sandbox (100,000 objects, 1 GB memory, 10 GB disk, 1 collection); BSD-3-Clause core free to self-host |
| Paid from | Standard: usage-based, billed hourly on vCPU, RAM, disk and backups | Flex from $45/mo pay-as-you-go; Premium prepaid contract, minimum from $400/mo |
| Has API | ✓ | ✓ |
| Open source | ✓ | ✓ |
| Free to use | ✓ | ✓ |
| Users | — | — |
| Founded | 2021 | 2019 |
| Maker | Independent (Qdrant Solutions GmbH) | — |
| Verdict | Qdrant is one of the strongest open-source vector databases, especially where search has to be combined with complex filters, and its free cloud cluster and permissive licence make it easy to start. Its performance claim... |
Weaviate pairs vector similarity with BM25 keyword search in a single query, and its built-in vectorizer modules mean you are not always wiring your own embedding pipeline. G2 reviewers rate it 4.4 out of 5 across 49 rev... |
| Full review → | Directory listing → |
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Comparisons cover up to 4 tools. Scores are RECATOOLS editorial assessments; verify current pricing on each vendor's site.