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Database Operations

This section documents the database operations and data persistence services that the NDF Studio system depends on.

Overview

The NDF Studio system uses database services for:

  • Data persistence and storage
  • User data management
  • Graph data storage and retrieval
  • Transaction management
  • Data backup and recovery

External Dependencies

Database Systems and Services

  • File System Storage: Primary data storage using JSON/YAML files
  • SQLite: Lightweight database for metadata and indexing
  • PostgreSQL: Relational database (if used for production)
  • Redis: Caching and session storage
  • Backup Services: Data backup and recovery systems

Core Database Functions

  • CRUD Operations: Create, Read, Update, Delete operations
  • Transaction Management: Ensuring data consistency
  • Query Optimization: Efficient data retrieval
  • Data Validation: Ensuring data integrity
  • Backup and Recovery: Data protection and restoration

Integration Points

Data Storage Architecture

  1. File-based Storage: JSON/YAML files for graph data
  2. Registry Management: Centralized metadata storage
  3. User Data Isolation: Per-user data organization
  4. Atomic Operations: Ensuring data consistency
  5. Backup Systems: Regular data protection

Data Management

  • User Data: User-specific graphs and configurations
  • Global Data: Shared templates and schemas
  • System Data: Configuration and metadata
  • Temporary Data: Cache and session information
  • Backup Data: Historical versions and recovery points

Configuration

Database operations are configured through: - Storage path configuration - Database connection settings - Backup and recovery policies - Performance optimization settings - Security and access controls

Features

Data Persistence

  • Atomic Writes: Ensuring data consistency
  • Version Control: Tracking data changes
  • Rollback Capability: Reverting to previous states
  • Data Validation: Ensuring data quality
  • Compression: Optimizing storage space

Performance Optimization

  • Caching: Frequently accessed data caching
  • Indexing: Fast data retrieval
  • Query Optimization: Efficient data access patterns
  • Connection Pooling: Managing database connections
  • Load Balancing: Distributing database load