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FastFind.NET

Ultra-high performance cross-platform file search library for .NET 10

License .NET Build Status

Packages

Package Version Description
FastFind.Core NuGet Core interfaces, SIMD string matching, StringPool
FastFind.Windows NuGet NTFS MFT direct access, USN Journal sync
FastFind.Unix NuGet Linux/macOS parallel enumeration, file monitoring
FastFind.SQLite NuGet Disk-backed persistent index

Key Features

  • Cross-Platform SIMD: Vector256/Vector128 auto-dispatch (AVX2, SSE2, NEON) — 1.87M ops/sec
  • MFT Direct Access (Windows): 31K+ files/sec NTFS enumeration, 30x faster than standard APIs
  • Parallel BFS Enumeration (Linux/macOS): Channel-based depth-aware parallel traversal
  • Real-Time Monitoring: USN Journal (Windows) / inotify (Linux) / FSEvents (macOS)
  • Disk-Backed Index: Keep the index in SQLite instead of memory — footprint stays flat as the corpus grows
  • Memory Optimized: paths and names are interned, so a repeated directory prefix is stored once
  • Auto Platform Detection: ModuleInitializer auto-registration

Installation

dotnet add package FastFind.Core

# Platform-specific (auto-registered at runtime)
dotnet add package FastFind.Windows    # Windows
dotnet add package FastFind.Unix       # Linux / macOS

dotnet add package FastFind.SQLite     # Optional: persistent index

Quick Start

using FastFind;

// Platform auto-detected — creates Windows, Linux, or macOS engine
using var engine = FastFinder.CreateSearchEngine();

await engine.StartIndexingAsync(new IndexingOptions
{
    SpecificDirectories = [@"D:\Projects"],         // Windows
    // MountPoints = ["/home", "/opt"],             // Linux / macOS
    ExcludedPaths = ["node_modules", ".git", "bin", "obj"],
    CollectFileSize = true
});

while (engine.IsIndexing) await Task.Delay(500);

var results = await engine.SearchAsync(new SearchQuery
{
    BasePath = @"D:\Projects",
    SearchText = "controller",
    ExtensionFilter = ".cs",
    MaxResults = 100
});

await foreach (var file in results.Files)
{
    Console.WriteLine($"{file.Name} ({file.SizeFormatted}) - {file.DirectoryPath}");
}

Keeping the index on disk

By default the index lives in memory. Give the engine a persistence store and it answers queries from disk instead, so its footprint does not grow with the number of indexed files:

using FastFind;
using FastFind.SQLite;

await using var store = SqlitePersistence.Create(@"D:\cache\index.db");
await store.InitializeAsync();

using var engine = FastFinder.CreateSearchEngine(store);

// Index once; the store survives the process.
await engine.StartIndexingAsync(new IndexingOptions { SpecificDirectories = [@"D:\Projects"] });
while (engine.IsIndexing) await Task.Delay(500);

Console.WriteLine($"{engine.Index!.Count} files indexed, {engine.Index.MemoryUsage} bytes held in memory");

Pass PersistenceMode.MirrorInMemory instead to keep the in-memory index for speed and use the store purely for durability — that costs the memory of both, and is the right choice only when the corpus comfortably fits.

The engine does not dispose a store you created; you keep ownership.

A store is safe to use from several threads or tasks at once — searching while indexing needs no coordination from the caller, because each operation takes its own pooled connection. See the concurrency notes for what a transaction covers and the one shape that is not supported.

Performance

Metric Windows Linux macOS
SIMD String Matching 1.87M ops/sec 1.87M ops/sec 1.87M ops/sec
File Enumeration 31K files/sec (MFT) Channel BFS parallel Channel BFS parallel
Search Operations 1.68M ops/sec 1.68M ops/sec 1.68M ops/sec
Memory per Op 439 bytes 439 bytes 439 bytes

Platform Support

Platform Status Package
Windows 10/11, Server 2019+ Production FastFind.Windows
Linux (Ubuntu, RHEL, Alpine) Preview FastFind.Unix
macOS (Ventura+) Preview FastFind.Unix

Documentation

License

MIT License - see LICENSE for details.

About

Ultra-high performance cross-platform .NET file search library — SIMD-optimized string matching, direct NTFS MFT access on Windows, SQLite FTS5 indexing, and real-time monitoring.

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