Amazon ElastiCache vs Kafka

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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.

- No public GitHub repository available -

What is Amazon ElastiCache?

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.

What is Kafka?

Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design.
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    What are some alternatives to Amazon ElastiCache and Kafka?
    Redis
    Redis is an open source, BSD licensed, advanced key-value store. It is often referred to as a data structure server since keys can contain strings, hashes, lists, sets and sorted sets.
    Elasticsearch
    Elasticsearch is a distributed, RESTful search and analytics engine capable of storing data and searching it in near real time. Elasticsearch, Kibana, Beats and Logstash are the Elastic Stack (sometimes called the ELK Stack).
    Memcached
    Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.
    Azure Redis Cache
    It perfectly complements Azure database services such as Cosmos DB. It provides a cost-effective solution to scale read and write throughput of your data tier. Store and share database query results, session states, static contents, and more using a common cache-aside pattern.
    MemCachier
    MemCachier provides an easy and powerful managed caching solution for all your performance and scalability needs. It works with the ubiquitous memcache protocol so your favourite language and framework already supports it.
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    Decisions about Amazon ElastiCache and Kafka
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    How developers use Amazon ElastiCache and Kafka
    Avatar of Pinterest
    Pinterest uses KafkaKafka

    http://media.tumblr.com/d319bd2624d20c8a81f77127d3c878d0/tumblr_inline_nanyv6GCKl1s1gqll.png

    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.

    Avatar of Volkan Özçelik
    Volkan Özçelik uses Amazon ElastiCacheAmazon ElastiCache

    I use a micro elesticache instance as a shared session store between the Node.js clusters of dojo.zerotoherojs.com and nightly.zerotoherojs.com

    Avatar of Coolfront Technologies
    Coolfront Technologies uses KafkaKafka

    Building out real-time streaming server to present data insights to Coolfront Mobile customers and internal sales and marketing teams.

    Avatar of Cloud Consultant
    Cloud Consultant uses Amazon ElastiCacheAmazon ElastiCache

    Audit the ElastiCache configurations for best practices and standards.

    Avatar of Binded
    Binded uses Amazon ElastiCacheAmazon ElastiCache

    We use ElastiCache to run Redis, which we use as a queue through Kue.

    Avatar of ShareThis
    ShareThis uses KafkaKafka

    We are using Kafka as a message queue to process our widget logs.

    Avatar of Christopher Davison
    Christopher Davison uses KafkaKafka

    Used for communications and triggering jobs across ETL systems

    Avatar of theskyinflames
    theskyinflames uses KafkaKafka

    Used as a integration middleware by messaging interchanging.

    Avatar of Instacart
    Instacart uses Amazon ElastiCacheAmazon ElastiCache

    We use Elasticache. Both Redis and Memchached.

    Avatar of Bùi Thanh
    Bùi Thanh uses Amazon ElastiCacheAmazon ElastiCache
    • Redis cluster for cache and session storage
    How much does Amazon ElastiCache cost?
    How much does Kafka cost?
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