WILD Database

Cache-Resident Ultra-High-Performance Key-Value Store with Authentication & Replication

WILD (Within-cache Incredibly Lightweight Database) is a production-ready high-performance key-value store designed to reside entirely in CPU L3 cache memory, achieving sub-microsecond latencies with comprehensive security and replication features.

Quick Start

# 1. Build WILD
zig build

# 2. Start primary database with authentication
./zig-out/bin/wild --auth-secret mysecret --enable-wal --wal-path primary.wal

# 3. Connect with client
./zig-out/bin/wild-client-example health

Performance Characteristics

Benchmark Results (Ryzen 9 7800X3D, 96MB L3 Cache)

Operation	Latency	Throughput
Single Read	20ns/op	349.0M ops/sec
Single Write	42ns/op	23.6M ops/sec
Batch Operations	2-28ns/op	620M+ ops/sec

Key Metrics:

• Sub-microsecond latencies for all operations
• 620M+ ops/sec total throughput
• Cache-optimized storage sized to fit entirely in L3 cache

Architecture

WILD leverages modern CPU architecture for extreme performance:

Core Design

• Cache-Line Aligned Records: 64-byte records fit exactly in CPU cache lines
• Flat Hash Storage: Linear probing with bitwise operations
• NUMA Awareness: Automatic CPU topology detection and optimization
• Zero Runtime Allocation: Static allocator eliminates allocation overhead
• Lock-Free Operations: Atomic primitives for concurrent access
• Replication: Primary-replica model for read scaling
• Durability: Write-ahead log with async batching
• Snapshots: Point-in-time recovery system
• High Concurrency: 100,000+ concurrent connections via io_uring (requires Linux)

Security & Authentication

WILD includes a simple authentication system:

# Start database with authentication required
./zig-out/bin/wild --auth-secret "your-secure-secret-here" --port 7878

# All clients must authenticate
./zig-out/bin/wild-client-example --auth-secret "your-secure-secret-here"

Security Features:

• Shared secret authentication for all connections
• Timing-attack resistant
• Replication authentication
• Connection-level access control

See docs/SECURITY.md for detailed security information.

Replication & High Availability

WILD supports primary-replica replication for read scaling:

Primary Node

# Start as primary with replication enabled
./zig-out/bin/wild \
  --mode primary \
  --auth-secret mysecret \
  --enable-wal \
  --wal-path primary.wal \
  --replication-port 9001

Replica Node

# Start as replica connecting to primary
./zig-out/bin/wild \
  --mode replica \
  --auth-secret mysecret \
  --primary-address 192.168.1.100 \
  --primary-port 9001

Replication Features:

• Read Scaling: Distribute read load across replicas
• Real-time Sync: WAL-based replication with minimal lag
• Automatic Failover: Client-side replica health monitoring

See docs/REPLICATION.md for replication setup and management.

Usage Examples

Standalone Database

# Basic standalone database
./zig-out/bin/wild --capacity 1000000 --auth-secret mysecret

Production Primary-Replica Setup

# Primary (write node)
./zig-out/bin/wild \
  --mode primary \
  --capacity 2000000 \
  --auth-secret "production-secret" \
  --enable-wal \
  --wal-path /data/wild-primary.wal \
  --port 7878 \
  --replication-port 9001

# Replica 1 (read node)
./zig-out/bin/wild \
  --mode replica \
  --auth-secret "production-secret" \
  --primary-address primary.example.com \
  --primary-port 9001 \
  --port 7879

# Replica 2 (read node)
./zig-out/bin/wild \
  --mode replica \
  --auth-secret "production-secret" \
  --primary-address primary.example.com \
  --primary-port 9001 \
  --port 7880

Client Usage

# Health check
./zig-out/bin/wild-client-example health

# Load testing
./zig-out/bin/wild-client-example load-test

# Replication testing
./zig-out/bin/wild-client-example replication-test

🛠️ Build & Installation

Prerequisites

• Zig 0.14+
• Linux x86-64 (other platforms unsupported, PRs welcome)
• CPU with L3 cache (more cache = higher capacity)
  • Storage space sizing is based on 75% of available L3 cache, divided by one cache line (64 bytes) then rounded down to the largest power of two that fits.
    • e.g., 96MB L3 cache means 72MB / 64 bytes = 1,179,648 records; rounded down to power of 2 is 1,048,576 records (2^20). Means space occupied in memory for data is 64MB.

Building

# Build all binaries
zig build

# Build with optimizations
zig build -Doptimize=ReleaseFast

# Available binaries after build:
# - ./zig-out/bin/wild              (main database daemon)
# - ./zig-out/bin/wild-client-example (example client)

Testing

# Run performance benchmarks
zig run quick_benchmark.zig -O ReleaseFast
zig run performance_benchmark.zig -O ReleaseFast

# Test replication
zig run replication_test.zig -O ReleaseFast

# Test recovery
zig run recovery_benchmark.zig -O ReleaseFast

Documentation

Document	Description
docs/WIRE_PROTOCOL.md	Binary protocol specification
docs/REPLICATION.md	Replication setup and management
docs/SECURITY.md	Authentication and security features
docs/API.md	Client API reference

Use Cases

WILD is optimized for specific high-performance scenarios:

Perfect For

• Cache-like workloads: Session stores, temporary data
• Read-heavy applications: Content delivery, catalog data
• Ultra-low latency: Trading systems, real-time analytics
• High-throughput services: Ad serving, recommendation engines
• Small datasets: You're limited to 52 bytes of data for the data you store in each record

Not Suitable For

• Large datasets: Must fit entirely in L3 cache
• Complex queries: Key-value operations only
• ACID transactions: Single-operation/batch consistency only
• Cross-platform: Linux x86-64 supported

Performance Tuning

Capacity Planning

# Check L3 cache size
./zig-out/bin/wild --help  # Shows detected cache size

# Set capacity
./zig-out/bin/wild --capacity 500000  # ~32MB for 500k records

Hardware Optimization

• L3 Cache: More L3 cache = higher database capacity
• Memory: Ensure sufficient RAM for WAL and OS buffers
• CPU: Higher core count improves concurrent throughput
• Storage: NVMe SSD recommended for WAL files

License

MIT License - see LICENSE for details.

Contributing

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

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

See our contribution guidelines for more information.

Support

• Issues: GitHub Issues
• Documentation: See docs/ directory
• Performance: Run benchmarks on your hardware