Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Most widely deployed open-source vector database with massive community
- Mature ELK stack ecosystem with extensive integrations and tools
- DiskBBQ algorithm enables efficient vector search without full in-memory indexes
- Powerful hybrid search combining keyword, filters, and vector similarity
- Consumption-based pricing—pay only for what you use
Cons
- Can be complex to configure and optimize for vector search
- Not purpose-built for vector search—added as a feature
- Resource-intensive at scale without proper optimization
- Pricing model complexity with multiple tiers and factors
Pros
- Unified platform: operational and vector data in one database
- Powerful hybrid search combining vector, metadata filters, graph, geospatial, and text search
- Independent scaling of vector search workloads for optimized performance
- Generous free tier (M0) for testing and development
- Enterprise-grade security and high availability built-in
Cons