Amazon ElastiCache vs Kafka: What are the differences?
Developers describe Amazon ElastiCache as "Deploy, operate, and scale an in-memory cache in the cloud". ElastiCache improves the performance of web applications by allowing you to retrieve information from fast, managed, in-memory caches, instead of relying entirely on slower disk-based databases. ElastiCache supports Memcached and Redis. On the other hand, Kafka is detailed as "Distributed, fault tolerant, high throughput pub-sub messaging system". Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
Amazon ElastiCache and Kafka are primarily classified as "Managed Memcache" and "Message Queue" tools respectively.
Some of the features offered by Amazon ElastiCache are:
- Support for two engines: Memcached and Redis
- Ease of management via the AWS Management Console. With a few clicks you can configure and launch instances for the engine you wish to use.
- Compatibility with the specific engine protocol. This means most of the client libraries will work with the respective engines they were built for - no additional changes or tweaking required.
On the other hand, Kafka provides the following key features:
- Written at LinkedIn in Scala
- Used by LinkedIn to offload processing of all page and other views
- Defaults to using persistence, uses OS disk cache for hot data (has higher throughput then any of the above having persistence enabled)
"Redis" is the primary reason why developers consider Amazon ElastiCache over the competitors, whereas "High-throughput" was stated as the key factor in picking Kafka.
Kafka is an open source tool with 12.5K GitHub stars and 6.7K GitHub forks. Here's a link to Kafka's open source repository on GitHub.
According to the StackShare community, Kafka has a broader approval, being mentioned in 501 company stacks & 451 developers stacks; compared to Amazon ElastiCache, which is listed in 342 company stacks and 79 developer stacks.
What is Amazon ElastiCache?
What is Kafka?
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Front-end messages are logged to Kafka by our API and application servers. We have batch processing (on the middle-left) and real-time processing (on the middle-right) pipelines to process the experiment data. For batch processing, after daily raw log get to s3, we start our nightly experiment workflow to figure out experiment users groups and experiment metrics. We use our in-house workflow management system Pinball to manage the dependencies of all these MapReduce jobs.
I use a micro elesticache instance as a shared session store between the Node.js clusters of dojo.zerotoherojs.com and nightly.zerotoherojs.com
Building out real-time streaming server to present data insights to Coolfront Mobile customers and internal sales and marketing teams.
Audit the ElastiCache configurations for best practices and standards.