⚡ Faster.Map — High-Performance HashMap for .NET

Faster.Map is a blazing-fast, memory-efficient HashMap library for .NET. It’s built to outperform Dictionary<TKey,TValue> and ConcurrentDictionary<TKey,TValue> by providing SIMD acceleration, lock-free concurrency, and custom hashing algorithms.

Designed for real-time systems, game engines, caching layers, and data-intensive applications, Faster.Map delivers exceptional speed, scalability, and predictable performance across varying load factors.

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🚀 Why Faster.Map?

The goal of Faster.Map is to create a more efficient and performant alternative to .NET’s built-in Dictionary and ConcurrentDictionary. While those are reliable, they can struggle under high-density workloads, frequent concurrent operations, or tight memory constraints.

Faster.Map solves those problems by providing specialized implementations optimized for different workloads.

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🧩 Available Implementations

DenseMap – SIMD-Accelerated Lookups

Harnesses SIMD (Single Instruction, Multiple Data) instructions for parallel key comparisons, drastically reducing lookup latency. ✅ Best for high-density datasets, real-time lookups, and CPU-bound workloads.

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RobinHoodMap – Linear Probing Strategy

Uses Robin Hood hashing to evenly distribute probe distances, minimizing clustering. ✅ Ideal for retrieval-heavy applications and balanced workloads.

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CMap – Lock-Free Concurrent HashMap

A thread-safe, lock-free, open-addressing HashMap using quadratic probing and Fibonacci hashing. ✅ Perfect for multi-threaded environments requiring high throughput and minimal contention.

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BlitzMap – Flat Open-Addressing HashMap

Employs a linked bucket approach similar to separate chaining but optimized for cache locality and collision resilience. ✅ The fastest all-round implementation, ideal for general-purpose and low-latency workloads.

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📜 Table of Contents

• Available Implementations
• Installation
• Basic Usage
• Advanced Usage
• Selecting the Right Hashmap
• Tested Platforms
• Benchmarks

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📦 Installation

Install Faster.Map via NuGet:

Install-Package Faster.Map

Supports .NET 6+, .NET 8, .NET Framework 4.8, and cross-platform (x86, x64, ARM, ARM64).

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🧠 Basic Usage Examples

Example: Using BlitzMap

var map = new BlitzMap<int, string>();
map.Insert(1, "Value One");
map.Insert(2, "Value Two");
map.InsertUnique(3, "Value Four");
map.InsertOrUpdate(2, "Updated");

if (map.Get(1, out var value))
    Console.WriteLine($"Key 1 has value: {value}");

map.Update(1, "Updated value one");
map.Remove(1);

var n = new BlitzMap<uint, uint>();
n.Insert(1,1);
map.Copy(n);

Example: Using DenseMap

var map = new DenseMap<int, string>();
map.Emplace(1, "Value One");
map.Emplace(2, "Value Two");

if (map.Get(1, out var value))
    Console.WriteLine($"Key 1 has value: {value}");

map.Remove(1);

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🧩 Advanced Usage

🔑 Custom Hashing Algorithms

Faster.Map supports pluggable hash functions for maximum performance:

• WyHash – High-speed general purpose hashing.
• XXHash3 – Optimized for throughput and low latency.
• FastHash – AES-based hashing (requires X86Aes support).

Example:

var map = new BlitzMap<int, string, XxHash3StringHasher>();
map.Insert(1, "Value One");
map.Insert(2, "Value Two");

All hashers are in the Faster.Map.Hasher namespace. 👉 Custom hashing significantly improves lookup speed and reduces collisions in large datasets.

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🧱 Tested on Platforms

• x86
• x64
• ARM
• ARM64

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🧮 Selecting the Right HashMap

Implementation	Best Use Case
DenseMap	High-density datasets, SIMD-accelerated lookups
RobinHoodMap	Retrieval-heavy workloads, stable latency
CMap	Lock-free multi-threaded performance
BlitzMap	General-purpose speed and consistent performance

✅ Recommendation:
Use BlitzMap for balanced performance, DenseMap for dense tables, RobinHoodMap for read-heavy workloads, and CMap for multi-threaded use.

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🧪 Benchmarks

(All benchmarks executed with BenchmarkDotNet v0.13.12 on .NET 9, Intel i5-12500H)

These benchmarks demonstrate how Faster.Map compares to Dictionary<TKey,TValue> across GET, INSERT, UPDATE, REMOVE, and ENUMERATE workloads at various load factors.

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📊 Get Benchmark

🏆 BlitzMap is the most consistent performer across all load factors.
🚀 DenseMap excels at high densities via SIMD acceleration.
⚠️ RobinhoodMap collapses after 0.5 load factor.
🔻 Dictionary suffers from excessive collisions.

Conclusion:
For balanced workloads, choose BlitzMap; for dense workloads, choose DenseMap.

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📊 Insert Benchmark

🏆 BlitzMap remains the fastest overall.
🚀 DenseMap shines at high load factors.
⚠️ RobinHoodMap degrades above 0.5.
🔻 Dictionary performs poorly under heavy loads.

Conclusion:
BlitzMap is the best general performer; DenseMap dominates full tables.

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📊 Update Benchmark

🏆 BlitzMap leads beyond 0.5 load factor.
⚡ RobinhoodMap dominates at lower densities.
🚀 DenseMap struggles at low densities due to SIMD overhead.

Conclusion:
Use RobinhoodMap for sparse data; BlitzMap for dense updates.

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📊 Remove Benchmark

🏆 RobinhoodMap offers best scaling for removals.
🚀 Dictionary wins at low densities.
⚠️ DenseMap performs worst at high load factors.

Conclusion:
Choose RobinhoodMap for removal-heavy workloads.

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📊 Enumerable Benchmark

🏆 BlitzMap is fastest across all load factors.
⚡ RobinhoodMap and DenseMap degrade significantly at high densities.

Conclusion:
For frequent iteration, BlitzMap is unmatched.

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📊 Get String Benchmark

🏆 BlitzMap scales best; Dictionary wins at low density.
🚀 DenseMap struggles with string hashing.

Conclusion:
For large string keys, use BlitzMap.

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📊 Get String Custom Hash Benchmark

🏆 BlitzMap + FastHash is fastest overall.
🧠 WyHash and XXHash3 perform better than defaults.

Conclusion:
Use FastHash for best string lookup performance.

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📊 Get Large String Benchmark

🏆 Dictionary dominates at low load factors.
🚀 BlitzMap maintains performance at high densities.
⚠️ DenseMap degrades quickly.

Conclusion:
Dictionary wins for small tables; BlitzMap wins for scalability.

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📊 Large String Custom Hash Benchmark

🏆 BlitzMapFastHash is the clear winner.
WyHash and XXHash3 are strong alternatives.
Dictionary performs worst at scale.

Conclusion:
For high-performance string key lookups, BlitzMapFastHash delivers the best scalability and speed.

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