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Vector Databases

FluidGrids provides comprehensive support for vector databases, enabling efficient similarity search and embedding management.

Supported Providers​

Milvus​

  • Features
    • Billion-scale Vectors
    • ANNS Search
    • Dynamic Schema
    • Hybrid Search
    • Real-time Search
  • Configuration
  • Performance Tuning
  • Best Practices

Pinecone​

  • Features
    • Managed Service
    • Auto-scaling
    • Hybrid Search
    • Metadata Filtering
    • Real-time Updates
  • Setup Guide
  • Query Optimization
  • Use Cases

Weaviate​

  • Features
    • Schema-based
    • Multi-modal
    • GraphQL API
    • RESTful API
    • Contextual Search
  • Implementation
  • Performance Tips
  • Examples

Integration Features​

Embedding Management​

  • Generation
    • Text Embeddings
    • Image Embeddings
    • Multi-modal Embeddings
  • Storage
  • Versioning
  • Updates

Search Capabilities​

  • Similarity Search
  • Hybrid Search
  • Filtered Search
  • Semantic Search
  • Faceted Search
  • Range Queries

Performance​

  • Index Optimization
  • Query Performance
  • Caching Strategies
  • Load Balancing
  • Scaling Options

Implementation Guide​

Setup​

  1. Provider Selection
  2. Database Configuration
  3. Schema Design
  4. Index Configuration
  5. Security Setup

Data Management​

  1. Data Ingestion
  2. Embedding Generation
  3. Index Building
  4. Data Updates
  5. Maintenance

Query Optimization​

  1. Query Design
  2. Performance Tuning
  3. Caching Strategy
  4. Error Handling
  5. Monitoring