AWS, Cloud Computing

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Enhancing Performance and Reducing Costs with Amazon ElastiCache


In the realm of database management, businesses frequently encounter the dual challenge of optimizing costs while simultaneously enhancing application performance. As data volumes expand and user bases grow, this challenge becomes more pronounced. For internet-scale applications grappling with vast amounts of data and high throughput demands, a robust underlying data architecture is indispensable. Improved application performance not only fosters better user experiences but also facilitates cost-effective business growth and market expansion.

One common strategy to address this challenge is the integration of a distributed result-set cache into the database infrastructure. Companies like Grab, Wiz, and DBS Bank leverage Amazon ElastiCache for Redis alongside their primary databases to bolster real-time application performance cost-effectively. Amazon ElastiCache, a fully managed, Redis-compatible service, offers real-time, optimized performance for modern applications. With the capacity to scale to hundreds of millions of operations per second and microsecond response times, ElastiCache ensures enterprise-grade security and reliability. It caters to diverse use cases ranging from accelerating application and database performance to serving as a primary datastore for scenarios where data durability is not paramount.

In this article, we delve into the intricacies of optimizing relational database costs through in-memory caching using Amazon ElastiCache. The insights presented herein are based on benchmarking tests conducted on Amazon Relational Database Service (Amazon RDS) for MySQL version 8.0.28 on instance type db.r6g.xlarge, wherein query results were cached in Amazon ElastiCache.

Amazon ElastiCache for Redis

Amazon ElastiCache stands as AWS’s native, purpose-built caching service, designed to complement primary databases and enhance overall performance while ensuring rapid scalability. Key features of ElastiCache include:

  • Exceptional Speed: Operating as an in-memory cache, Amazon ElastiCache boasts sub-millisecond response times.
  • Scalability: It offers both vertical and horizontal scalability to meet varying workload demands seamlessly.
  • Full Managed Service: Amazon ElastiCache handles hardware and software management effortlessly, including minor compute engine version upgrades. It ensures high availability with multi-AZ capability, autoscaling for variable workloads, and support for data tiering and reserved instance types.
  • Compatibility: Amazon ElastiCache seamlessly integrates with open-source Redis, ensuring compatibility and ease of use.

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Cost Optimization of Amazon RDS for MySQL with Amazon ElastiCache

Integrating ElastiCache, a caching solution, with relational databases such as Oracle, SQL Server, or Amazon RDS for MySQL yields significant performance improvements while reducing costs. According to studies, implementing ElastiCache with Amazon RDS for MySQL can result in savings of up to 55% in costs and up to 80 times faster read performance compared to using Amazon RDS for MySQL alone.

By caching result sets and offloading database IOPS, ElastiCache effectively enhances both database and application performance. It proves to be more cost-effective than scaling database instance capacity, with a single ElastiCache node capable of processing over 250,000 requests per second. Workloads characterized by heavy reads and common database queries returning the same result set stand to benefit immensely from query result caching.

However, not all database workloads are suitable for caching. Write-heavy databases dominated by inserts or updates, as well as applications reliant on database-level processing, may not derive significant benefits from caching. Nevertheless, ElastiCache proves invaluable for applications requiring:

  • Handling massive throughput volumes.
  • Managing spiky traffic patterns.
  • Processing large volumes of data in real-time before database updates.
  • Ensuring instantaneous user response times.

Implementing ElastiCache with Primary Data Sources

Amazon ElastiCache can seamlessly integrate with various data sources, including relational databases like MySQL, Oracle, PostgreSQL, SQL Server, NoSQL databases like Amazon DynamoDB or Amazon DocumentDB (with MongoDB compatibility), Amazon Simple Storage Service (Amazon S3), or even distributed computing applications that eschew traditional databases.

Reduce Read Replica Footprint and Save Costs with ElastiCache

By replacing Amazon RDS for MySQL read replicas with a fully distributed ElastiCache cluster, businesses can achieve comparable levels of read capacity at a lower cost with superior performance. ElastiCache’s dedicated memory, network, and CPU resources contribute to significantly lower latency and higher throughput. Importantly, only query results, rather than entire database sets, need to be cached, eliminating the necessity for full database replication.

Strategies for Caching Implementation

Businesses can adopt various caching strategies tailored to their application requirements:

  • Lazy Load Caching: This prevalent strategy, also known as lazy population or cache-aside caching, involves populating the cache only when the application requests an object. It entails querying the cache first, followed by the database if the object is not found—a process optimized for minimizing database calls.
  • Write-Through Caching: Ideal for workloads necessitating consistency, the write-through strategy ensures cache refreshment upon data mutations in the source datastore. Client applications update the database and subsequently read the updated data back, synchronously caching the new query results. Time-to-live (TTL) expiration mechanisms are often employed to maintain data consistency.


The cost savings realized through the integration of Amazon ElastiCache with primary relational databases like Amazon RDS are directly proportional to the application’s read throughput requirements. As read throughput increases, scaling relational databases becomes increasingly expensive.

Conversely, each Amazon ElastiCache node can support a throughput of up to 400,000 Queries Per Second (QPS), offering both performance gains and cost reductions.

Drop a query if you have any questions regarding Amazon ElastiCache and we will get back to you quickly.

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1. Does Amazon ElastiCache support edge cases such as write-heavy databases or applications relying on database-level processing?

ANS: – While Amazon ElastiCache is highly effective for read-heavy workloads and applications requiring instantaneous response times, it may not be suitable for write-heavy databases dominated by insert or update operations. Similarly, applications heavily reliant on database-level processing, such as those utilizing stored procedures and triggers, may not experience significant benefits from caching with Amazon ElastiCache.

2. Can Amazon ElastiCache seamlessly integrate with non-relational databases or distributed computing applications?

ANS: – Yes, Amazon ElastiCache can integrate not only with relational databases like MySQL and PostgreSQL but also with non-relational databases such as Amazon DynamoDB or Amazon DocumentDB. Additionally, it can be utilized in distributed computing applications where traditional databases are not utilized, offering caching capabilities to enhance performance and reduce latency.

WRITTEN BY Vineet Negi

Vineet Negi is a Research Associate at CloudThat. He is part of the Kubernetes vertical and has worked on DevOps and many other Cloud Computing technologies. He is an enthusiastic individual who is passionate about exploring all the latest technologies from a learning perspective.



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