Vector Databases in Enterprise: Selection and Implementation Guide

Vector databases power semantic search and RAG systems. Choosing the right one matters.

Options Landscape

• Pinecone: Managed, simple, but vendor lock-in
• Weaviate: Open-source, feature-rich
• Milvus: High performance, complex operations
• pgvector: PostgreSQL extension, familiar tooling

Selection Criteria

1. Scale requirements (vectors, queries/second)
2. Operational complexity tolerance
3. Hybrid search needs (vector + keyword)
4. Existing infrastructure (Kubernetes, managed services)

Implementation Patterns

• Embedding versioning and migration
• Index tuning for recall vs latency
• Backup and disaster recovery
• Multi-tenancy considerations

Performance Optimization

Vector search performance depends on index type, vector dimensions, and hardware. Benchmark with realistic data before production deployment.