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Explain the Cache Pattern.

Anubhav Sharma 275 08 Apr 2026

Explain the Cache Pattern.

Anubhav Sharma

Student

The Anubhav portal was launched in March 2015 at the behest of the Hon'ble Prime Minister for retiring government officials to leave a record of their experiences while in Govt service .

1 Answers

Ravi Vishwakarma 09 Apr 2026

Advanced Redis Caching Patterns

We’ll cover the most important patterns:

Cache Aside (Lazy Loading)
Write Through
Write Behind (Write Back)
Read Through
Refresh Ahead

1. Cache Aside (Lazy Loading) – Most Common

How it works

App checks cache first
If cache miss → fetch from DB → store in cache → return
If cache hit → return directly

Flow

Client → API → Cache → (Miss) → DB → Cache → Response

Example (ASP.NET Core)

public async Task<Product> GetProductAsync(int id)
{
    string key = $"product_{id}";

    var cached = await _cacheService.GetAsync<Product>(key);
    if (cached != null)
        return cached;

    var product = await _dbContext.Products.FindAsync(id);

    if (product != null)
        await _cacheService.SetAsync(key, product, TimeSpan.FromMinutes(10));

    return product;
}

Pros

Simple and flexible
Full control over caching logic

Cons

Cache inconsistency possible
Extra DB call on miss

2. Write Through

How it works

Data is written to cache and DB at the same time

Flow

Client → API → Cache → DB → Response

Example

public async Task UpdateProductAsync(Product product)
{
    await _dbContext.SaveChangesAsync();

    string key = $"product_{product.Id}";
    await _cacheService.SetAsync(key, product, TimeSpan.FromMinutes(10));
}

Pros

Cache always up-to-date
Strong consistency

Cons

Slower writes
More load on cache

3. Write Behind (Write Back)

How it works

Write goes to cache first
DB update happens asynchronously (background job)

Flow

Client → API → Cache → Queue → Background Worker → DB

Use Case

High write-heavy systems (logs, analytics)

Example Idea

await _cacheService.SetAsync(key, product);

// Push to queue (RabbitMQ / BackgroundService)
await _queue.PublishAsync(product);

Background worker:

public async Task ProcessQueue()
{
    var product = await _queue.ConsumeAsync();
    await _dbContext.SaveChangesAsync();
}

Pros

Very fast writes
Scales well

Cons

Risk of data loss
Eventual consistency

4. Read Through

How it works

Cache layer itself fetches data from DB
App never directly calls DB

Flow

Client → API → Cache Layer → DB → Cache → Response

Note

ASP.NET Core does NOT support this natively—you need a custom abstraction layer.

Pros

Cleaner architecture
Centralized caching logic

Cons

Complex implementation
Less control at API level

5. Refresh Ahead (Proactive Caching)

How it works

Cache is refreshed before expiration

Flow

Cache nearing expiry → Background refresh → Update cache

Example

public async Task RefreshCacheAsync()
{
    var products = await _dbContext.Products.ToListAsync();
    await _cacheService.SetAsync("product_list", products, TimeSpan.FromMinutes(10));
}

Run via:

Hosted Service (IHostedService)
Hangfire / Quartz.NET

Pros

No cache misses
Fast response always

Cons

Extra processing
May cache unused data

Pattern Comparison

Pattern	Read Speed	Write Speed	Consistency	Complexity
Cache Aside	Fast	Medium	Medium	Low
Write Through	Fast	Slow	High	Medium
Write Behind	Fast	Very Fast	Low	High
Read Through	Fast	Medium	High	High
Refresh Ahead	Very Fast	Medium	High	Medium

Which Pattern Should You Use?

Use Cache Aside if:

General web apps
Blog / CMS / APIs (your case likely)

Use Write Through if:

Data must always be consistent
Financial / transactional systems

Use Write Behind if:

High write traffic
Analytics / logging

Use Refresh Ahead if:

High-read systems
Frequently accessed data

Production Best Practices

Always use cache key naming strategy
Implement cache invalidation
Use distributed locks to avoid cache stampede
Add fallback mechanism
Monitor Redis memory & TTL

Recommended Architecture (Real-World)

For most ASP.NET Core apps:

Cache Aside + Refresh Ahead
Redis Distributed Cache
Background Worker (for refresh)
SQL Server as source of truth

Final Thoughts

Using Redis effectively is not just about caching—it’s about choosing the right pattern based on your system’s behavior.

A wrong pattern can:

Cause stale data
Increase load
Break consistency

A right pattern can:

Make your API 10x faster
Reduce DB cost
Scale effortlessly

forum

Explain the Cache Pattern.

Can you answer this question?

1 Answers

Advanced Redis Caching Patterns

1. Cache Aside (Lazy Loading) – Most Common

How it works

Flow

Example (ASP.NET Core)

Pros

Cons

2. Write Through

How it works

Flow

Example

Pros

Cons

3. Write Behind (Write Back)

How it works

Flow

Use Case

Example Idea

Pros

Cons

4. Read Through

How it works

Flow

Note

Pros

Cons

5. Refresh Ahead (Proactive Caching)

How it works

Flow

Example

Pros

Cons

Pattern Comparison

Which Pattern Should You Use?

Use Cache Aside if:

Use Write Through if:

Use Write Behind if:

Use Refresh Ahead if:

Production Best Practices

Recommended Architecture (Real-World)

Final Thoughts