Aurora

A high-performance in-memory database with built-in role management for Rust applications.

Notice

⚠️ This crate is in early development.

Features

• High Performance: Optimized in-memory storage for blazing-fast read and write operations
• Role-Based Access Control: Built-in role management system for fine-grained permissions
• Type Safety: Leverages Rust's type system for compile-time guarantees
• Zero-Copy Operations: Minimizes memory overhead for maximum efficiency
• Concurrent Access: Thread-safe operations with minimal locking overhead

Use Cases

• Caching layer with access control
• Session management with role-based permissions
• Real-time applications requiring fast data access
• Microservices needing lightweight, embedded databases
• Development and testing environments

Getting Started

Add Aurora to your Cargo.toml:

[dependencies]
aurora = "*"

Roadmap

• Phase 1: Persistence Layer

  • Snapshot Storage: Periodic memory snapshots to disk
  • Write-Ahead Logging (WAL): Transaction log for crash recovery
  • Configurable Persistence: Choose between speed and durability
  • Data Compression: Efficient storage with compression algorithms
  • Incremental Backups: Fast backup and restore capabilities

• Phase 2: Advanced Query & Indexing

  • Secondary Indexes: Support for multiple index types (B-tree, hash, etc.)
  • Query Language: SQL-like query interface for complex operations
  • Full-Text Search: Built-in text search capabilities
  • Aggregation Functions: COUNT, SUM, AVG, and custom aggregations
  • Query Optimization: Query planning and execution optimization

• Phase 3: Graph Database Integration

  • Graph Data Model: Native support for nodes and edges
  • Graph Traversal API: Efficient path finding and pattern matching
  • Graph Algorithms: PageRank, shortest path, community detection
  • Cypher-like Query Language: Graph-specific query interface
  • Hybrid Storage: Seamlessly combine relational and graph data

• Phase 4: Data Warehouse Features

  • Columnar Storage: Column-oriented storage for analytical queries
  • OLAP Operations: Support for cube, rollup, and drill-down operations
  • Data Partitioning: Horizontal partitioning for large datasets
  • ETL Pipeline: Built-in extract, transform, load capabilities
  • Time-Series Optimization: Specialized storage for time-series data
  • Analytics Functions: Window functions and statistical operations

• Phase 5: Distributed & Scalability

  • Replication: Support replication
  • Sharding: Automatic data distribution across nodes
  • Cluster Management: Node discovery and health monitoring
  • Distributed Transactions: ACID guarantees across nodes
  • Load Balancing: Intelligent query routing

• Phase 6: Integration

  • Data streaming: Real-time streaming data ingestion
  • Monitoring & Metrics: Prometheus/Grafana integration
  • REST/GraphQL API: HTTP-based access layer
  • TimeScale: Time-travel queries and historical data analysis

Examples

Aurora includes several examples to help you get started:

• basic_usage - Simple CRUD operations and role management
• search_by_value - Simple product catalog with search options

Run any example with:

cargo run --example basic_usage

License

This project is licensed under the MIT License.