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💾 Storage

Last Updated: 2025-01-19

Overview of databases commonly used in AI applications, from vector stores to relational databases.

Vector Databases​

Qdrant​

  • Provider: Qdrant
  • Website: qdrant.tech
  • GitHub: github.com/qdrant/qdrant
  • Deployment: Cloud and Self-hosted
  • Key Features:
    • High-performance vector similarity search
    • Filtering with payload
    • Horizontal scalability
    • REST API and gRPC interfaces
    • Cloud and self-hosted options
  • Pricing: qdrant.tech/pricing
    • Free tier available
    • Cloud starts at $30/month
    • Enterprise: Custom pricing

Pinecone​

  • Provider: Pinecone
  • Website: pinecone.io
  • Deployment: Cloud
  • Key Features:
    • Managed vector database
    • Real-time updates
    • Hybrid search
    • Metadata filtering
    • Serverless architecture
  • Pricing: pinecone.io/pricing
    • Starter: Free tier
    • Standard: Usage-based pricing
    • Enterprise: Custom pricing

RDBMS (Relational Database Management Systems)​

Supabase​

  • Provider: Supabase
  • Website: supabase.com
  • GitHub: github.com/supabase/supabase
  • Deployment: Cloud and Self-hosted
  • Key Features:
    • PostgreSQL database
    • Real-time subscriptions
    • Auto-generated APIs
    • Authentication
    • Storage
    • Vector embeddings support
  • Pricing: supabase.com/pricing
    • Free tier available
    • Pro: $25/month
    • Team: $599/month
    • Enterprise: Custom pricing