FastCache.Cached 1.1.1

There is a newer version of this package available.
See the version list below for details.
dotnet add package FastCache.Cached --version 1.1.1                
NuGet\Install-Package FastCache.Cached -Version 1.1.1                
This command is intended to be used within the Package Manager Console in Visual Studio, as it uses the NuGet module's version of Install-Package.
<PackageReference Include="FastCache.Cached" Version="1.1.1" />                
For projects that support PackageReference, copy this XML node into the project file to reference the package.
paket add FastCache.Cached --version 1.1.1                
#r "nuget: FastCache.Cached, 1.1.1"                
#r directive can be used in F# Interactive and Polyglot Notebooks. Copy this into the interactive tool or source code of the script to reference the package.
// Install FastCache.Cached as a Cake Addin
#addin nuget:?package=FastCache.Cached&version=1.1.1

// Install FastCache.Cached as a Cake Tool
#tool nuget:?package=FastCache.Cached&version=1.1.1                


CI/CD nuget

High-performance, thread-safe and simple to use caching library that scales with ease from tens to tens of millions of items. Features include automatic eviction, lock-free and wait-free access and storage, allocation-free access and low memory footprint. Credit and thanks to Vladimir Sadov for his implementation of NonBlocking.ConcurrentDictionary which is used as a backing store.

Quick start

dotnet add package FastCache.Cached or Install-Package FastCache.Cached

Get cached value or save a new one with expiration of 60 minutes

public FinancialReport GetReport(int month, int year)
  if (Cached<FinancialReport>.TryGet(month, year, out var cached))
    return cached.Value;

  var report = // Expensive computation: retrieve data and calculate report

  return cached.Save(report, TimeSpan.FromMinutes(60));

Wrap a regular method call

var report = Cached.GetOrCompute(month, year, GetReport, TimeSpan.FromMinutes(60));

Or an async one

// For methods that return Task<T> or ValueTask<T>
var report = await Cached.GetOrCompute(month, year, GetReportAsync, TimeSpan.FromMinute(60));

Add new data without accessing cache item first (e.g. loading a large batch of independent values to cache)

using FastCache.Extensions;
foreach (var ((month, year), report) in reportsResultBatch)
  report.Cache(month, year, TimeSpan.FromMinutes(60));

Store common type (string) in a shared cache store (OK for small (<1M) to mid (<5M) sized collections)

// GetOrCompute<T...> where T is string
var userNote = Cached.GetOrCompute(userId, GetUserNoteString, TimeSpan.FromMinutes(5));

Or in a separate one by using value object (Recommended)

readonly record struct UserNote(string Value);

// GetOrCompute<T...> where T is UserNote
var userNote = Cached.GetOrCompute(userId, GetUserNote, TimeSpan.FromMinutes(5));
// This is how it looks for TryGet
if (Cached<UserNote>.TryGet(userId, out var cached))
  return cached.Value;
return cached.Save(userNote, TimeSpan.FromMinutes(5));

Features and design philosophy

  • In-memory cache for items with expiration time and automatic eviction
  • Little to no ceremony - no need to configure or initialize, just add the package and you are ready to go. Behavior can be further customized via env variables
  • Focused design allows to reduce memory footprint per item and minimize overhead via inlining and static dispatch
  • High performance and scaling covering both simplest applications and highly loaded services. Can handle 1-100M+ items with O(1) access/storage time and O(n~) memory cost/cpu time cost for full eviction
  • Lock-free and wait-free get and add/update of cached items. Performance will improve with threads, data synchronization cost is minimal thanks to 'NonBlocking.ConcurrentDictionary' backing store by Vladimir Sadov
  • Multi-key store access without collisions between key types. Collisions are avoided by statically dispatching on the composite key type signature e.g. string, CustomEnum, int together with the type of cached value
  • Handles timezone/dst updates on most platforms by relying on system uptime timestamp for item expiration - Environment.TickCount64 which is also significantly faster than DateTime.UtcNow

Access / Store latency and cost at throughput saturation

BenchmarkDotNet=v0.13.1, OS=Windows 10.0.22000
AMD Ryzen 7 5800X, 1 CPU, 16 logical and 8 physical cores
.NET 6.0.5 (6.0.522.21309), X64 RyuJIT
Method Mean Error StdDev Median Gen 0 Gen 1 Allocated
Get: FastCache.Cached 15.92 ns 0.367 ns 0.941 ns 15.31 ns - - -
Get: MemoryCache 86.74 ns 2.227 ns 6.565 ns 89.43 ns 0.0019 - 32 B
Get: CacheManager 167.03 ns 3.395 ns 9.002 ns 162.56 ns 0.0105 - 176 B
Get: LazyCache 74.46 ns 1.510 ns 2.214 ns 74.81 ns - - -
Add/Upd: FC.Cached 34.57 ns 0.920 ns 2.711 ns 33.73 ns 0.0024 - 40 B
Add/Upd: MemoryCache 778.21 ns 16.728 ns 49.060 ns 775.08 ns 0.4082 0.0038 6,832 B
Add/Upd: CacheManager 1,052.22 ns 20.926 ns 27.209 ns 1,053.61 ns 0.0744 - 1,248 B
Add/Upd: LazyCache 281.60 ns 3.984 ns 3.532 ns 281.79 ns 0.0286 - 480 B


  • FastCache.Cached add and update operations are represented by single cached.Save(param1...param7, expiration) which will either add or replace existing value updating its expiration
  • Comparison was made with a string-based key. Composite keys supported by FastCache.Cached have significant performance cost if they have reference types which incurs 30-40ns extra cpu cost per each reference typed param
  • CacheManager library provides methods with highly inconsistent performance and allocation characteristics. The method for it was chosen on the basis of closest functionality to 'non-throwing add or update'
  • Overall performance stays relatively comparable when downgrading to .NET 5 and decreases further by 15-30% when using .NET Core 3.1 with the difference ratio between libraries staying close to provided above
  • Non-standard platforms (the ones that aren't CLR based) use DateTime.UtcNow fallback instead of Environment.TickCount64, which will perform slower depending on the platform-specific implementation

On benchmark data

Throughput saturation means that all necessary data structures are fully available in the CPU cache and branch predictor has learned branch patters of the executed code. This is only possible in scenarios such as items being retrieved or added/updated in a tight loop or very frequently on the same cores. This means that real world performance will not saturate maximum throughput and will be bottlenecked by memory access latency and branch misprediction stalls. As a result, you can expect resulting performance variance of 1-10x min latency depending on hardware and outside factors.

Product Compatible and additional computed target framework versions.
.NET net5.0 is compatible.  net5.0-windows was computed.  net6.0 is compatible.  net6.0-android was computed.  net6.0-ios was computed.  net6.0-maccatalyst was computed.  net6.0-macos was computed.  net6.0-tvos was computed.  net6.0-windows was computed.  net7.0 is compatible.  net7.0-android was computed.  net7.0-ios was computed.  net7.0-maccatalyst was computed.  net7.0-macos was computed.  net7.0-tvos was computed.  net7.0-windows was computed.  net8.0 was computed.  net8.0-android was computed.  net8.0-browser was computed.  net8.0-ios was computed.  net8.0-maccatalyst was computed.  net8.0-macos was computed.  net8.0-tvos was computed.  net8.0-windows was computed. 
.NET Core netcoreapp3.0 was computed.  netcoreapp3.1 is compatible. 
.NET Standard netstandard2.1 is compatible. 
MonoAndroid monoandroid was computed. 
MonoMac monomac was computed. 
MonoTouch monotouch was computed. 
Tizen tizen60 was computed. 
Xamarin.iOS xamarinios was computed. 
Xamarin.Mac xamarinmac was computed. 
Xamarin.TVOS xamarintvos was computed. 
Xamarin.WatchOS xamarinwatchos was computed. 
Compatible target framework(s)
Included target framework(s) (in package)
Learn more about Target Frameworks and .NET Standard.

NuGet packages

This package is not used by any NuGet packages.

GitHub repositories

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