Cache Aside

🧠 Cache-Aside Pattern (Lazy Loading) — Explained

Cache-Aside (also known as Lazy Loading) is a caching strategy where your application explicitly loads data into the cache only when needed — typically on a cache miss.

---

💡 Simple Definition

“You look in the cache. If it’s not there, you go to the database, get the data, store it in the cache, and return it.”

---

🔄 How Cache-Aside Works

1. App asks: “Is the data in cache?”
   → If YES → return it ✅
   → If NO → fetch from DB ⛔

2. After DB fetch:
   → Store the data in cache ✅
   → Return it to user

---

🧱 Typical Flow

// Pseudocode
function getData(key):
    data = cache.get(key)
    if data is null:
        data = db.query(key)
        cache.set(key, data)
    return data

---

✏️ Write Flow

In cache-aside, writes and updates go directly to the database, and the cache is either:

• Invalidated (deleted), or

• Updated manually

function updateData(key, newValue):
    db.update(key, newValue)
    cache.delete(key) // or cache.set(key, newValue)

---

✅ Advantages

• Simple and flexible

• Avoids caching infrequently accessed data (saves memory)

• Good control over when/what to cache

---

❌ Disadvantages

• Cache miss penalty on first request

• Risk of stale data if you don’t invalidate cache correctly

• Extra code complexity to manage both cache and DB access

---

🔁 Cache-Aside vs Write-Through vs Write-Behind

Strategy	On Read	On Write	Sync With DB	Risk of Staleness
Cache-Aside	Load on miss	Write to DB, invalidate cache	Manual sync	Medium
Write-Through	Always cached	Write to cache + DB	Immediate	Low
Write-Behind	Always cached	Write to cache, delay DB	Async	High (until flush)

---

🛠️ When to Use Cache-Aside

• Read-heavy systems with occasional writes

• When you want fine-grained control over cache population

• Situations where data may change frequently, and cache needs to stay fresh

---

📦 Real-World Examples

• Product pages in an e-commerce site

• Profile data in social media apps

• News articles or blog posts