VecLabs vs the alternatives
Feature comparison
| Feature | VecLabs | Pinecone | Qdrant | Weaviate |
|---|---|---|---|---|
| Query engine | Rust HNSW | Proprietary | Rust HNSW | Go |
| p99 latency (1536 dims) | 4.7ms | ~30ms | ~18ms | ~48ms |
| Monthly cost (1M vectors) | ~$0.25 | $70 | $25+ | $25+ |
| Client-side encryption | ✅ | ❌ | ❌ | ❌ |
| On-chain audit trail | ✅ | ❌ | ❌ | ❌ |
| Data ownership | Your wallet | Their servers | Their servers | Their servers |
| Open source | ✅ MIT | ❌ | ✅ Apache 2 | ✅ BSD |
| Self-hostable | ✅ | ❌ | ✅ | ✅ |
| Metadata filtering | 📋 Planned | ✅ | ✅ | ✅ |
| Hybrid search | 📋 Planned | ✅ | ✅ | ✅ |
| Managed cloud | ❌ | ✅ | ✅ | ✅ |
| TypeScript SDK | ✅ | ✅ | ✅ | ✅ |
| Python SDK | ✅ | ✅ | ✅ | ✅ |
When to choose VecLabs
Choose VecLabs if:- Latency matters - you need sub-5ms queries in production
- Cost matters - you’re storing millions of vectors
- Privacy matters - your vectors should be unreadable to the provider
- Auditability matters - you need proof of data integrity
- You’re building AI agents that need persistent, verifiable memory
- You need metadata filtering today (VecLabs has it planned)
- You want a fully managed service with enterprise SLAs
- Your team has no interest in open-source infrastructure
- You want open-source with mature metadata filtering
- You’re self-hosting and need advanced features
- You don’t need cryptographic proof
A note on fairness
Pinecone and competitor numbers in this comparison are estimated from public benchmarks and documentation. VecLabs numbers are measured directly - methodology and reproduction steps inbenchmarks/COMPARISON.md. Reach out if you find any inaccuracies.