KacheDB Documentation

The High-Performance, Zero-Copy In-Memory Engine for Redis-Compatible Caching & LLM KV-Cache Offloading

📖 Welcome to the KacheDB Documentation

KacheDB is an open-source, next-generation in-memory storage engine engineered from first principles in Rust. It bridges the gap between traditional microsecond application caching (Redis / Valkey workloads) and multi-gigabyte tensor state offloading for Large Language Model (LLM) inference engines (vLLM, SGLang, PyTorch).

🗺️ Documentation Sitemap

🚀 Getting Started

• Quickstart Guide: Build from source, run via Cargo or Docker, and query via CLI.
• kachedb-cli User Guide: Interactive terminal REPL and built-in throughput benchmark harness.
• Server Configuration & Tuning: Worker threads, CPU pinning, memory pool sizing, and kernel bypass settings.

⚡ Command Reference

• Core Key-Value Commands: GET, SET, MGET, MSET, DEL, EXISTS, INCR, DECR, APPEND, STRLEN, DBSIZE, TYPE, FLUSHDB, FLUSHALL, PING.
• TTL & Key Lifecycle Commands: EXPIRE, PEXPIRE, EXPIREAT, PEXPIREAT, TTL, PTTL, PERSIST, and the background Timing Wheel.
• SIMD Semantic Vector Commands: VADD, VSEARCH, VADD_BATCH, VSEARCH_BATCH, VDEL, VSTATS, VINDEX, ARM NEON / AVX2 kernels.
• Server Observability & Introspection: INFO, COMMAND DOCS, HELLO 2/3, AUTH, CLIENT SETNAME/GETNAME/ID/LIST, BGREWRITEAOF, QUIT.

🏛️ System Architecture

• System Architecture Overview: High-level system design, thread-per-core model, and the physical memory hierarchy.
• 2 MB Megaslab Memory Engine: Slotted slab bump allocator, 64-byte cache-line alignment, and S3-FIFO quota manager.
• Token Radix Prefix Tree: Hierarchical &[u32] token prefix tree, sub-microsecond prefill lookup, and Epoch RCU concurrency.
• Zero-Copy Shared Memory IPC: POSIX /dev/shm lock-free ring buffers and PCIe line-rate tensor sharing.

🤖 Production Integration Guides

• vLLM Integration Guide: Drop-in PagedAttention KV connector for vLLM inference servers.
• SGLang Integration Guide: RadixAttention tree-branching prefill offloading with SGLang.
• Semantic Caching Guide: High-throughput sync and async prompt caching with kachedb-py and FastEmbed/HuggingFace.

📊 Performance & Benchmarks

• Consolidated Master Benchmark Report: Criterion micro-benchmarks, latency percentiles, and hardware comparisons against Redis 7.4, Valkey 8.0, and DragonflyDB.
• Benchmark Artifacts & Logs: Raw test outputs, multi-phase scaling reports, and reproducibility scripts.