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  1. Stackups
  2. Utilities
  3. Caching
  4. Managed Memcache
  5. Amazon ElastiCache vs Hazelcast

Amazon ElastiCache vs Hazelcast

OverviewComparisonAlternatives

Overview

Amazon ElastiCache
Amazon ElastiCache
Stacks1.3K
Followers1.0K
Votes151
Hazelcast
Hazelcast
Stacks427
Followers474
Votes59
GitHub Stars6.4K
Forks1.9K

Amazon ElastiCache vs Hazelcast: What are the differences?

Introduction

Amazon ElastiCache and Hazelcast are both popular in-memory data caching solutions that provide high performance and scalability for applications. However, there are key differences between these two technologies that make them suitable for different use cases.

  1. Data Persistence: Amazon ElastiCache supports data persistence to Amazon S3, allowing you to store cache data even when the cache cluster is restarted. Hazelcast, on the other hand, does not provide built-in data persistence mechanisms.

  2. Cloud Support: Amazon ElastiCache is a fully managed service provided by AWS, which means it is tightly integrated with other AWS services and is highly scalable. In contrast, Hazelcast can be deployed on-premises or in various cloud environments, offering more flexibility in terms of deployment options.

  3. Ease of Use: Amazon ElastiCache offers a simple and intuitive API that makes it easy to integrate with applications running on AWS. It also provides seamless integration with other AWS services, such as Amazon CloudWatch for monitoring and AWS Identity and Access Management (IAM) for access control. Hazelcast, while also having a user-friendly interface, may require more configuration and setup for integration with different environments.

  4. Language Support: Amazon ElastiCache is optimized for Java applications and provides native language clients for Java, .NET, Python, Ruby, Node.js, and PHP. Hazelcast, on the other hand, supports a wider range of programming languages including Java, .NET, C++, Python, Node.js, and more, making it more versatile for developers using different language stacks.

  5. Cluster Management: Amazon ElastiCache offers automatic cluster management, allowing you to easily scale your cache cluster up or down and handle node failures without manual intervention. Hazelcast also supports cluster management features, but it may require more configuration and monitoring from the user's side.

  6. Pricing Model: Amazon ElastiCache has a pay-as-you-go pricing model, which charges you based on the size and number of cache nodes you use. Hazelcast, on the other hand, offers both open-source and enterprise versions, with the enterprise version providing additional features and support but requiring a subscription.

In summary, Amazon ElastiCache is a fully managed service provided by AWS with built-in data persistence and tight integration with other AWS services. It is optimized for Java applications and offers simple cluster management. Hazelcast, on the other hand, is more versatile in terms of language support, allowing developers to choose from a wider range of programming languages and deployment options. It is suitable for both on-premises and cloud environments but may require more configuration and setup compared to Amazon ElastiCache.

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Detailed Comparison

Amazon ElastiCache
Amazon ElastiCache
Hazelcast
Hazelcast

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.

With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.

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.;Detailed monitoring statistics for the engine nodes at no extra cost via Amazon CloudWatch;Pay only for the resources you consume based on node hours used
Distributed implementations of java.util.{Queue, Set, List, Map};Distributed implementation of java.util.concurrent.locks.Lock;Distributed implementation of java.util.concurrent.ExecutorService;Distributed MultiMap for one-to-many relationships;Distributed Topic for publish/subscribe messaging;Synchronous (write-through) and asynchronous (write-behind) persistence;Transaction support;Socket level encryption support for secure clusters;Second level cache provider for Hibernate;Monitoring and management of the cluster via JMX;Dynamic HTTP session clustering;Support for cluster info and membership events;Dynamic discovery, scaling, partitioning with backups and fail-over
Statistics
GitHub Stars
-
GitHub Stars
6.4K
GitHub Forks
-
GitHub Forks
1.9K
Stacks
1.3K
Stacks
427
Followers
1.0K
Followers
474
Votes
151
Votes
59
Pros & Cons
Pros
  • 58
    Redis
  • 32
    High-performance
  • 26
    Backed by amazon
  • 21
    Memcached
  • 14
    Elastic
Pros
  • 11
    High Availibility
  • 6
    Distributed Locking
  • 6
    Distributed compute
  • 5
    Sharding
  • 4
    Load balancing
Cons
  • 4
    License needed for SSL
Integrations
No integrations available
Java
Java
Spring
Spring

What are some alternatives to Amazon ElastiCache, Hazelcast?

Redis

Redis

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

Aerospike

Aerospike

Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.

MemSQL

MemSQL

MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.

Apache Ignite

Apache Ignite

It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale

MemCachier

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.

SAP HANA

SAP HANA

It is an application that uses in-memory database technology that allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows it to process data stored in RAM as opposed to reading it from a disk.

Memcached Cloud

Memcached Cloud

Memcached Cloud is a fully-managed service for running your Memcached in a reliable and fail-safe manner. Your dataset is constantly replicated, so if a node fails, an auto-switchover mechanism guarantees data is served without interruption. Memcached Cloud provides various data persistence options as well as remote backups for disaster recovery purposes.

VoltDB

VoltDB

VoltDB is a fundamental redesign of the RDBMS that provides unparalleled performance and scalability on bare-metal, virtualized and cloud infrastructures. VoltDB is a modern in-memory architecture that supports both SQL + Java with data durability and fault tolerance.

Tarantool

Tarantool

It is designed to give you the flexibility, scalability, and performance that you want, as well as the reliability and manageability that you need in mission-critical applications

Azure Redis Cache

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.

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