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Amazon Web Services - Introduction to Elastic Cache

Last Updated : 18 Jun, 2026

Amazon ElastiCache is a fully managed in-memory caching service provided by AWS for fast and real-time applications. It helps improve application performance by storing frequently accessed data in memory.

  • Stores data in RAM instead of disks for much faster read and write speeds.
  • Supports Redis OSS, Valkey, and Memcached for easy integration with applications.
  • Works as a fast cache layer in front of databases like Amazon RDS and DynamoDB.
  • Supports clustering for high availability and better scaling.
  • Provides a serverless option that automatically scales based on application traffic.
👁 aws_elastic_cache

Note: Caching is the process of storing frequently accessed data in a temporary, high-speed data storage layer known as a cache.

Redis vs. Memcached

Redis and Memcached are two popular in-memory caching engines used to improve application performance and reduce data access time. Both provide fast caching, but they differ in features, scalability, and supported use cases.

FeatureRedisMemcached
Data Type SupportSupports strings, lists, sets, hashes, and more.Supports only simple key-value data.
Data BackupCan save data using backups and recovery options.Does not save data permanently.
ReplicationSupports data replication and automatic failover.Does not support replication.
ScalingSupports clustering for better scaling.Scales by adding more nodes.
Messaging SupportSupports publish/subscribe messaging.Does not support messaging features.
PerformanceGood for advanced and real-time applications.Best for simple and fast caching.
Best Use CasesLeaderboards, analytics, sessions, and chat apps.Database query caching and temporary session storage.

Note: Use Redis for 95% of modern workloads. Select Memcached only if you require a simple, multi-threaded cache or need compatibility with a legacy Memcached codebase.

Cluster Mode Enabled vs. Disabled

Amazon ElastiCache Redis provides two cluster modes for managing data and scaling performance. The choice depends on application size, workload, and scalability needs.

FeatureCluster Mode DisabledCluster Mode Enabled
StructureOne primary node with up to 5 replicas.Multiple shards with primary and replica nodes.
Data StorageAll data is stored in a single node group.Data is divided across multiple shards.
Read ScalingAdd replicas to improve read performance.Add replicas or shards for better scaling.
Write ScalingScale by increasing instance size only.Scale by adding more shards horizontally.
Best ForSmall applications and simple setups.Large applications with heavy workloads.

Serverless vs. Provisioned

ElastiCache provides two deployment models: Serverless and Provisioned. The best choice depends on application traffic, scaling needs, and management preferences.

FeatureElastiCache ServerlessProvisioned ElastiCache
ManagementAWS automatically manages and scales resources.Users manually choose nodes and instance types.
ScalingAutomatically scales based on traffic.Scaling must be configured manually.
PricingPay for actual storage and usage.Pay a fixed cost for running nodes.
AvailabilityMulti-AZ enabled by default.Multi-AZ setup is configured manually.
Best ForApplications with changing or unpredictable traffic.Applications with stable and predictable workloads.

Caching Strategies

To use ElastiCache effectively, your application must implement an appropriate caching pattern:

Lazy Loading (Cache-Aside)

  • Mechanism: The application attempts to read from the cache first. If a cache miss occurs, the application queries the database, writes the retrieved data to the cache, and returns it to the client.
  • Pros: Memory is used efficiently since only requested data is cached.
  • Cons: The initial request suffers a performance penalty due to the round-trip database query.

Write-Through

  • Mechanism: The application writes new or updated data to both the database and the cache simultaneously.
  • Pros: Guarantees the cache is always updated, preventing dirty reads.
  • Cons: Increases write latency due to completing two consecutive write operations.

Accessing the Amazon ElastiCache Console

Step 1: Log in to the AWS management Console.

Step 2: In the search bar at the top, type ElastiCache

👁 Screenshot-2026-06-11-141303

Step 3: Click on Amazon ElastiCache from the search results.

👁 Screenshot-2026-06-11-141413

ElastiCache vs. DynamoDB DAX

While both are in-memory caching solutions, they differ in flexibility and integration scope. Amazon ElastiCache is a general-purpose caching service that works with different databases and applications, while DynamoDB DAX is a specialized cache designed only for Amazon DynamoDB to improve read performance.

FeatureElastiCache (Redis)DynamoDB DAX
PurposeGeneral cache for different databases and applications.Cache made only for Amazon DynamoDB.
Code ChangesRequires application code changes to manage caching.Only requires changing the DynamoDB endpoint.
FlexibilityCan store sessions, queues, leaderboards, and other data.Mainly stores DynamoDB query results.
Database SupportWorks with RDS, Aurora, DynamoDB, MongoDB, and more.Works only with DynamoDB.
PerformanceVery fast in-memory caching for many use cases.Improves DynamoDB read performance.
Use CasesGaming, chat apps, caching, sessions, analytics.Fast access to frequently used DynamoDB data.

Use Cases

  • Database Caching: Store frequently used database data to reduce load on databases like Amazon RDS and improve speed.
  • Session Storage: Save user login sessions and shopping cart data for quick access.
  • Live Leaderboards: Create fast and real-time rankings for games and applications using Redis.
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