RKVS - Rust Key-Value Storage

A high-performance, namespace-based key-value storage system built in Rust. RKVS provides persistent storage with configurable limits, async operations, and atomic batch processing.

Features

• 🚀 High Performance: Optimized for speed with async operations and efficient data structures
• 📁 Namespace Support: Organize data into isolated namespaces with individual configurations
• ⚡ Atomic Operations: Batch operations with all-or-nothing semantics
• 💾 Persistence: Optional file-based persistence with automatic serialization
• 🔒 Thread-Safe: Built on Tokio's async primitives for concurrent access
• 📊 Rich Metadata: Track key counts, sizes, and namespace statistics
• 🎯 Configurable Limits: Set per-namespace limits for keys and value sizes
• 🔄 Atomic Consume: Get and delete operations in a single atomic step

Quick Start

Add RKVS to your Cargo.toml:

[dependencies]
rkvs = "0.1.0"
tokio = { version = "1.0", features = ["full"] }

Basic Usage

use rkvs::{StorageManager, NamespaceConfig, Result};

#[tokio::main]
async fn main() -> Result<()> {
    // Create a storage manager
    let storage = StorageManager::builder()
        .with_persistence("/tmp/rkvs_data".into())
        .build();
    
    // Initialize the storage
    storage.initialize().await?;
    
    // Create a namespace with configuration
    let config = NamespaceConfig {
        max_keys: Some(1000),
        max_value_size: Some(1024 * 1024), // 1MB
    };
    let ns_hash = storage.create_namespace("my_app", Some(config)).await?;
    
    // Get the namespace handle
    let namespace = storage.namespace(ns_hash).await?;
    
    // Store data
    namespace.set("user:123".to_string(), b"John Doe".to_vec()).await?;
    
    // Retrieve data
    if let Some(data) = namespace.get("user:123").await {
        println!("User: {}", String::from_utf8_lossy(&data));
    }
    
    // Atomic consume (get and delete)
    if let Some(data) = namespace.consume("user:123").await {
        println!("Consumed: {}", String::from_utf8_lossy(&data));
        // Key is now deleted
    }
    
    Ok(())
}

Batch Operations

RKVS supports efficient batch operations for processing multiple key-value pairs:

use rkvs::{Namespace, BatchResult};

async fn batch_example(namespace: &Namespace) -> Result<()> {
    // Batch set multiple items
    let items = vec![
        ("key1".to_string(), b"value1".to_vec()),
        ("key2".to_string(), b"value2".to_vec()),
        ("key3".to_string(), b"value3".to_vec()),
    ];
    
    let result = namespace.set_multiple(items).await;
    if result.is_success() {
        println!("Set {} items successfully", result.total_processed);
    } else {
        println!("Errors: {:?}", result.errors);
    }
    
    // Batch get multiple items
    let keys = vec!["key1".to_string(), "key2".to_string(), "key3".to_string()];
    let result = namespace.get_multiple(keys).await;
    
    if let Some(data) = result.data {
        for (key, value) in data {
            println!("{}: {}", key, String::from_utf8_lossy(&value));
        }
    }
    
    Ok(())
}

Configuration

Configure storage and namespace limits:

use rkvs::{StorageConfig, NamespaceConfig};

// Global storage configuration
let storage_config = StorageConfig {
    max_namespaces: Some(100),
    default_max_keys_per_namespace: Some(10000),
    default_max_value_size: Some(10 * 1024 * 1024), // 10MB
};

// Per-namespace configuration
let namespace_config = NamespaceConfig {
    max_keys: Some(1000),
    max_value_size: Some(1024 * 1024), // 1MB
};

let storage = StorageManager::builder()
    .with_config(storage_config)
    .with_persistence("/data/rkvs".into())
    .build();

Performance

RKVS is designed for high performance with the following characteristics:

• Namespace Operations: ~370ns (create), ~427ns (get), ~457ns (delete)
• Key-Value Operations: ~790ns (small values), ~1.84μs (large values)
• Batch Operations: Linear scaling with 3-8% improvement over individual operations
• Concurrent Access: Optimized for read-heavy workloads with RwLock-based synchronization

See the benchmark results for detailed performance metrics.

API Reference

Core Types

• StorageManager: Main entry point for managing namespaces
• Namespace: Handle for working with a specific namespace
• NamespaceConfig: Configuration for namespace limits
• StorageConfig: Global storage configuration
• BatchResult<T>: Result of batch operations with metadata

Key Methods

StorageManager

• create_namespace(name, config) - Create a new namespace
• namespace(hash) - Get a namespace handle
• delete_namespace(hash) - Remove a namespace
• list_namespaces() - List all namespaces
• save() / load() - Persistence operations

Namespace

• set(key, value) - Store a key-value pair
• get(key) - Retrieve a value
• delete(key) - Remove a key
• exists(key) - Check if key exists
• consume(key) - Atomically get and delete
• set_multiple(items) - Batch set operation
• get_multiple(keys) - Batch get operation
• delete_multiple(keys) - Batch delete operation
• consume_multiple(keys) - Batch consume operation

Error Handling

RKVS uses a unified error type RkvsError with the following variants:

• Storage: File I/O and storage-related errors
• Serialization: Data serialization/deserialization errors
• Internal: Internal system errors

use rkvs::{Result, RkvsError};

async fn error_handling_example() -> Result<()> {
    match namespace.set("key".to_string(), b"value".to_vec()).await {
        Ok(()) => println!("Success"),
        Err(RkvsError::Storage(msg)) => println!("Storage error: {}", msg),
        Err(RkvsError::Serialization(msg)) => println!("Serialization error: {}", msg),
        Err(RkvsError::Internal(msg)) => println!("Internal error: {}", msg),
    }
    Ok(())
}

Thread Safety

RKVS is fully thread-safe and designed for concurrent access:

• All operations are async and can be safely called from multiple tasks
• Read operations can run concurrently within a namespace
• Write operations are serialized per namespace
• Batch operations provide atomicity guarantees

Persistence

RKVS supports optional file-based persistence:

let storage = StorageManager::builder()
    .with_persistence("/path/to/data".into())
    .build();

// Save all data to disk
storage.save().await?;

// Load data from disk
storage.load().await?;

Data is automatically serialized using bincode for efficient storage.

License

This project is licensed under the MIT License - see the LICENSE file for details.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Changelog

v0.1.0

• Initial release
• Namespace-based storage
• Async operations
• Batch processing
• File persistence
• Comprehensive benchmarking