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Furrow

An adaptive storage engine that optimizes itself in real-time.

Goals

  1. Efficient Storage Implementation - High-performance storage primitives designed for modern hardware.

  2. Real-time Parameter Tuning - Automatically adjusts configuration to achieve optimal performance for any workload.

  3. Full Hardware Utilization - Maximizes the use of all allocated hardware resources.

  4. Dynamic Resource Allocation - Supports online adjustment of hardware resource quotas while maintaining optimal workload performance.

Non-Goals

  1. Workload Pattern Detection - Furrow does not analyze or classify workload patterns. This responsibility belongs to upstream consumers.

  2. Distributed Storage - Furrow is a single-node storage engine. Distributed coordination and replication are out of scope.

Why Rust

We chose Rust for two key reasons:

  1. No Garbage Collection - GC languages introduce unpredictable latency spikes, making them unsuitable for high-performance storage systems where deterministic performance is critical.

  2. Best-in-class AI Agent Training Data - Among non-GC languages (C, C++, Rust), Rust has the highest quality training corpus for AI agents. This enables better automated code generation, review, and maintenance—critical for a project designed to be AI-assisted throughout its lifecycle.

License

Apache-2.0

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