Which cache engines are supported by Amazon ElastiCache?

Which cache engines are supported by Amazon ElastiCache?

Amazon ElastiCache supports two major open source in-memory caching engines: Memcached and Redis. ElastiCache users typically select between the two caching engines, depending on the design of the corresponding application. Memcached is a general-purpose distributed memory caching system for Linux, OS X and Windows.

Is NoSQL an ElastiCache?

Amazon ElastiCache is a web service that makes it easy to deploy, operate, and scale an in-memory data store or cache in the cloud. Redis is a leading in-memory NoSQL data store that supports persistence, availability, and Lua scripting.

How expensive is ElastiCache?

1 Answer. They certainly can be that expensive; for an ondemand instance pricing could be as low as around $12/month for a micro instance with ondemand pricing and as much as about $2750/month for a single r3.

How to determine what to cache in ElastiCache?

Data and access pattern – Determining what to cache also involves understanding the data itself and its access patterns. For example, it doesn’t make sense to cache data that changes quickly or is seldom accessed. For caching to provide a real benefit, the data should be relatively static and frequently accessed.

What kind of data store does Amazon ElastiCache use?

Amazon ElastiCache works as an in-memory data store and cache to support the most demanding applications requiring sub-millisecond response times. By utilizing an end-to-end optimized stack running on customer dedicated nodes, Amazon ElastiCache provides secure, blazing fast performance.

Is the Amazon ElastiCache service compatible with Memcached?

Amazon ElastiCache is protocol-compliant with Memcached and Redis, so code, applications, and popular tools that you use today with your existing Memcached or Redis environments will work seamlessly with the service.

What does Amazon ElastiCache for Redis do for You?

Amazon ElastiCache for Redis gives you a fast in-memory data store to help you build and deploy machine learning models quickly.