Caching strategies and services (for example, Amazon ElastiCache)

Task Statement 3.3: Determine high-performing database solutions.

📘AWS Certified Solutions Architect – (SAA-C03)

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What is Caching?

Caching is a way to store frequently used data in a fast storage layer so that applications can access it quickly instead of repeatedly querying slower databases. Think of it as a shortcut for data retrieval.

• Why use caching?
  1. Reduce latency: Access data faster than reading from the database every time.
  2. Reduce database load: Fewer database queries mean the database can handle more users.
  3. Improve scalability: Applications can handle sudden spikes in traffic.

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Types of Caching in AWS

AWS provides caching mainly through Amazon ElastiCache. There are two popular caching engines:

1. Redis (via ElastiCache for Redis)
2. Memcached (via ElastiCache for Memcached)

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1. Amazon ElastiCache for Redis

Redis is a key-value in-memory store. It is very fast and supports advanced features.

Key features:

• Persistence: Redis can save data to disk, so it’s not lost if the server restarts.
• Replication: Supports read replicas to distribute read traffic.
• Data structures: Can store strings, hashes, lists, sets, sorted sets, etc.
• Pub/Sub: Can be used for messaging between applications.
• High availability: Supports Redis Cluster and automatic failover.

Use cases in IT:

• Session storage: Keep user session data for web apps.
• Leaderboards: Quickly access sorted data for gaming or analytics.
• Caching database queries: Store results of expensive queries to reduce database load.

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2. Amazon ElastiCache for Memcached

Memcached is simpler than Redis. It is also an in-memory key-value store but is volatile (data is lost if server restarts) and does not support persistence.

Key features:

• High-speed caching: Excellent for read-heavy workloads.
• Simple architecture: Easy to set up and scale horizontally.
• Scalability: Can add more nodes to increase cache capacity.

Use cases in IT:

• Object caching: Cache API responses or database query results.
• Temporary storage: Keep temporary data that can be regenerated if lost.

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Caching Strategies

1. Lazy Loading (On-Demand)
   • Data is cached only when it is requested.
   • If data isn’t in cache, it’s retrieved from the database and stored in cache.
   • Pros: Efficient, only caches what’s needed.
   • Cons: First request is slower (cache miss).
2. Write-Through
   • Every write to the database also updates the cache.
   • Pros: Cache is always up to date.
   • Cons: Slightly slower writes, more complex.
3. Write-Around
   • Writes go directly to the database, not the cache.
   • Cache is updated only when data is read (lazy loading).
   • Pros: Avoids unnecessary caching of data that is rarely read.
   • Cons: Initial reads may be slower (cache miss).
4. Write-Back (Write-Behind)
   • Writes are made to the cache first, and the database is updated later asynchronously.
   • Pros: Fast writes, reduces database load.
   • Cons: Risk of data loss if cache fails before database update.

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ElastiCache Deployment Considerations

When using ElastiCache, consider:

• Cluster mode: Redis can be clustered for scaling horizontally.
• Multi-AZ deployment: For high availability, enable automatic failover.
• Node type and size: Choose based on memory and throughput requirements.
• TTL (Time to Live): Expire cached data to avoid stale data.
• Eviction policies: Define what happens when cache is full (LRU = Least Recently Used, etc.).

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AWS Exam Tips

1. Know the difference between Redis and Memcached:
   • Redis = advanced features, persistent, supports data structures.
   • Memcached = simple, volatile, fast, good for horizontal scaling.
2. Understand caching strategies: Lazy loading, write-through, write-around, write-back. The exam may give a scenario and ask which strategy fits best.
3. Performance impact: Caching is used to reduce database load and improve application speed.
4. Integration with other AWS services: ElastiCache is often used with:
   • Amazon RDS or DynamoDB for database query caching.
   • API Gateway / Lambda for serverless apps needing fast data access.
5. High availability and scaling: Know Multi-AZ, replication, and cluster mode for Redis.

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Quick Comparison Table for Exam

Feature	Redis	Memcached
Persistence	Yes	No
Advanced data structures	Yes	No
Scaling	Horizontal (cluster)	Horizontal
High availability	Multi-AZ & failover	No built-in failover
Use case	Session storage, leaderboards, pub/sub	Simple cache for queries

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✅ Summary:
Caching with ElastiCache improves performance by reducing database load and latency. Redis is feature-rich, persistent, and supports advanced use cases. Memcached is simpler, fast, and suitable for temporary caching. Choosing the right caching strategy and deployment design is critical for high-performing database solutions in AWS.