Caching in C#: How to Speed Up Your Application and Save Resources

Why Caching is a Superpower for Every C# Developer

Imagine: your application goes to the database every time for the same list of cities or exchange rates. A database is a slow and expensive resource. What if we told you that you could respond to the user in 1 millisecond instead of 100? Yes, this is not magic, but smart data caching in C#.

Caching is a technique of temporarily storing frequently requested data in fast storage (usually in RAM). In this article, we will look at how to implement caching in .NET applications using both built-in mechanisms and external solutions. You will learn how to choose the right strategy and avoid the trap of stale data.

Types of Caching in C#: From MemoryCache to Redis

In the .NET ecosystem, there are several approaches to caching. The choice depends on your application's architecture: monolith or microservices, single server or cluster.

1. Built-in MemoryCache (System.Runtime.Caching / Microsoft.Extensions.Caching.Memory)

The simplest and fastest way is to use IMemoryCache. Data is stored in the process's RAM. Ideal for single-threaded applications or simple websites.

Example of registration and usage in ASP.NET Core:

// In Program.cs\nbuilder.Services.AddMemoryCache();\n\n// In a controller or service\npublic class WeatherService\n{\n    private readonly IMemoryCache _cache;\n\n    public WeatherService(IMemoryCache cache)\n    {\n        _cache = cache;\n    }\n\n    public async Task<string> GetWeatherAsync(string city)\n    {\n        string cacheKey = $"weather_{city}";\n\n        // Try to get data from cache\n        if (_cache.TryGetValue(cacheKey, out string cachedData))\n        {\n            return cachedData;\n        }\n\n        // If data is not found — load it (e.g., from API)\n        string weatherData = await FetchWeatherFromApi(city);\n\n        // Save to cache for 10 minutes\n        var cacheEntryOptions = new MemoryCacheEntryOptions()\n            .SetAbsoluteExpiration(TimeSpan.FromMinutes(10));\n\n        _cache.Set(cacheKey, weatherData, cacheEntryOptions);\n\n        return weatherData;\n    }\n}

Key methods: TryGetValue, Set, Remove. Pay attention to expiration policies: absolute expiration (data dies exactly after N minutes) and sliding expiration (data lives as long as it is accessed, and for N minutes after the last request).

2. Distributed Cache: Redis via IDistributedCache

If you have multiple application instances (web farm, microservices), MemoryCache is not suitable — each server will store its own copy. Redis comes to the rescue. It works as a separate server, shared across all instances.

Connecting Redis in C#:

// Install the package: Microsoft.Extensions.Caching.StackExchangeRedis\nbuilder.Services.AddStackExchangeRedisCache(options =>\n{\n    options.Configuration = "localhost:6379";\n    options.InstanceName = "SampleInstance";\n});\n\n// Usage via IDistributedCache\npublic class ProductService\n{\n    private readonly IDistributedCache _cache;\n\n    public ProductService(IDistributedCache cache)\n    {\n        _cache = cache;\n    }\n\n    public async Task<Product> GetProductAsync(int id)\n    {\n        string cacheKey = $"product_{id}";\n        var cachedProduct = await _cache.GetStringAsync(cacheKey);\n\n        if (cachedProduct != null)\n        {\n            return JsonSerializer.Deserialize<Product>(cachedProduct);\n        }\n\n        var product = await FetchProductFromDb(id);\n        var serialized = JsonSerializer.Serialize(product);\n\n        await _cache.SetStringAsync(cacheKey, serialized, new DistributedCacheEntryOptions\n        {\n            AbsoluteExpirationRelativeToNow = TimeSpan.FromMinutes(30)\n        });\n\n