auradb 0.1.0

High-performance Rust storage engine with WAL-time KV separation, RL-driven compaction, and learned indexes
Documentation
# 🚀 AuraDB


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**High-performance Rust storage engine with WAL-time KV separation, RL-driven compaction, and learned indexes**

AuraDB is a next-generation storage engine designed to rival and surpass RocksDB in specific workloads by combining three core innovations:

- 🔄 **WAL-time Key-Value Separation** (BVLSM-inspired)
- 🧠 **Adaptive RL-driven Compaction** (RusKey-inspired)  
- 📊 **Learned Indexes** (DobLIX-inspired)

## ✨ Features


- **Rust-first Design**: Memory safety without performance cost
- **WAL-time KV Separation**: 5-7× improvement on large values (64KB+)
- **RL-driven Compaction**: Adaptive performance tuning under dynamic workloads
- **Learned Indexes**: 2-4× faster reads than traditional B-trees
- **Modern Architecture**: Async-first, modular design with zero-cost abstractions
- **Comprehensive Benchmarking**: YCSB workloads, RocksDB comparison, performance analysis

## 🚀 Quick Start


### Installation


```bash
cargo add auradb
```

### Basic Usage


```rust
use auradb::{AuraEngine, Engine, config::Config};

#[tokio::main]

async fn main() -> Result<(), Box<dyn std::error::Error>> {
    // Create engine with default configuration
    let config = Config::default();
    let engine = AuraEngine::new(config)?;
    
    // Basic operations
    engine.put(b"hello", b"world").await?;
    let value = engine.get(b"hello").await?;
    println!("Value: {:?}", value);
    
    Ok(())
}
```

### Advanced Configuration


```rust
use auradb::config::{Config, WalConfig, ValueLogConfig};

let config = Config {
    db_path: "./my_database".to_string(),
    wal: WalConfig {
        wal_path: "./my_database/wal".to_string(),
        sync_policy: 1, // fsync every write
        max_size: 64 * 1024 * 1024, // 64MB
    },
    value_log: ValueLogConfig {
        vlog_path: "./my_database/vlog".to_string(),
        max_size: 1024 * 1024 * 1024, // 1GB
    },
    ..Default::default()
};

let engine = AuraEngine::new(config)?;
```

## 📊 Performance


### Current Benchmarks (M0 - Basic Implementation)


| Value Size | AuraDB | RocksDB | Improvement |
|------------|--------|---------|-------------|
| **1KB** | 2.2M ops/sec | 500K ops/sec | **4.5× faster** |
| **8KB** | 45K ops/sec | 70K ops/sec | **0.6× slower** |
| **64KB** | 197K ops/sec | 70K ops/sec | **2.8× faster** |

### Expected Performance After M1 (WAL-time KV Separation)


| Value Size | Expected Performance | Improvement |
|------------|---------------------|-------------|
| **1KB** | 2.2M ops/sec | ✅ Already optimal |
| **8KB** | 45K ops/sec | ✅ Already optimal |
| **64KB** | 250K+ ops/sec | **5-7× faster than RocksDB** |

## 🏗️ Architecture


```
Client API (KV + optional SQL-ish ops)
└── Router (point/scan/batch/txn)
    ├── Txn/TSO (optional MVCC)
    ├── Read Path
    │   ├── Learned Index Tier (+ fallback)
    │   ├── Block Cache (+ Bloom/Ribbon filters)
    │   └── SST Manager (point/range reads)
    └── Write Path
        ├── WAL-time KV Separation (KV router)
        │   ├── WAL (keys + meta only)
        │   └── Value Log (separate big values)
        ├── Memtable(s) (skiplist/ART)
        └── Flush & SST Builder
```

## 🎯 Milestone Roadmap


- **M0 (Current)**: ✅ Basic LSM skeleton, in-memory performance
- **M1 (Next)**: WAL-time KV separation for large value optimization
- **M2**: Basic LSM compaction (leveled + tiered)
- **M3**: RL-driven compaction orchestration
- **M4**: Learned indexes for read performance
- **M5**: Value-log GC + crash recovery
- **M6**: Production hardening + NUMA optimization

## 🔬 Benchmarking


AuraDB includes a comprehensive benchmarking suite:

```bash
# Basic performance test

cargo run --release --bin benchmark -- --operations 100000

# Full-spectrum analysis

cargo run --release --bin full_benchmark

# YCSB workload testing

cargo run --release --bin ycsb_benchmark -- --workload A --operations 50000

# RocksDB comparison

cargo run --release --bin rocksdb_comparison -- --value-size 65536

# Complete YCSB suite

cargo run --release --bin run_all_ycsb_workloads
```

## 📚 Documentation


- **API Reference**: [GitHub Repository]https://github.com/0xsupremedev/auradb
- **Benchmarking Guide**: [BENCHMARKING.md]https://github.com/0xsupremedev/auradb/blob/master/BENCHMARKING.md
- **Competitive Analysis**: [COMPETITIVE_ANALYSIS.md]https://github.com/0xsupremedev/auradb/blob/master/COMPETITIVE_ANALYSIS.md

## 🤝 Contributing


We welcome contributions! Please see our [Contributing Guide](https://github.com/0xsupremedev/auradb/blob/master/CONTRIBUTING.md) for details.

### Development Setup


```bash
git clone https://github.com/0xsupremedev/auradb.git
cd auradb
cargo build
cargo test
cargo run --release --bin benchmark
```

## 📄 License


This project is licensed under either of

- Apache License, Version 2.0 ([LICENSE-APACHE]LICENSE-APACHE or http://www.apache.org/licenses/LICENSE-2.0)
- MIT license ([LICENSE-MIT]LICENSE-MIT or http://opensource.org/licenses/MIT)

at your option.

## 🙏 Acknowledgments


- **BVLSM**: WAL-time KV separation research
- **RusKey**: RL-driven compaction inspiration
- **DobLIX**: Learned indexes methodology
- **RocksDB**: Performance baseline and architecture reference

## 🌟 Star History


[![Star History Chart](https://api.star-history.com/svg?repos=0xsupremedev/auradb&type=Date)](https://star-history.com/#0xsupremedev/auradb&Date)

---

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