Azure Redis Cache vs Hazelcast

Overview

Hazelcast

Stacks427

Followers474

Votes59

GitHub Stars6.4K

Forks1.9K

Azure Redis Cache

Stacks58

Followers124

Votes7

Azure Redis Cache vs Hazelcast: What are the differences?

1. Scalability: Azure Redis Cache provides the ability to scale up or down based on the demand of the application, allowing users to easily handle varying workloads. On the other hand, Hazelcast offers both horizontal scaling, where additional nodes can be added to the cluster, and vertical scaling, where the size of individual nodes can be increased or decreased.
2. Data Persistence: Azure Redis Cache supports data persistence by offering options like RDB snapshots and AOF logs, which allow data to be stored even if the cache is restarted. Hazelcast also provides data persistence, but it does so through its built-in Map Store, which allows data to be stored in an external database or file system for durability.
3. Caching Strategies: Azure Redis Cache supports different caching strategies, such as LRU (Least Recently Used), LFU (Least Frequently Used), and custom eviction policies. Hazelcast, on the other hand, offers support for distributed caching with various eviction policies like LRU, LFU, and random eviction.
4. Integration with Microsoft Azure: Azure Redis Cache is a fully managed caching service provided by Microsoft Azure, allowing easy integration with other Azure services and providing features like high availability and automatic failover. In contrast, Hazelcast can be deployed on-premises or on any cloud platform, offering more flexibility in terms of deployment options.
5. Language Support: Azure Redis Cache provides support for multiple programming languages including .NET, Java, Node.js, Python, and more, making it accessible for developers using different technologies. Hazelcast also supports a wide range of programming languages, making it suitable for developers using different stacks and frameworks.
6. Security: Azure Redis Cache offers various security features, such as SSL/TLS encryption, Access Control Lists (ACLs), and Virtual Network Service Endpoints, ensuring confidentiality and restricting access to the cache. Hazelcast also provides security features like LDAP integration, SSL encryption, and network segregation to protect the cache and control access.

In summary, Azure Redis Cache and Hazelcast differ in terms of scalability, data persistence, caching strategies, integration with Microsoft Azure, language support, and security features.

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CLI (Node.js)

Manual

Detailed Comparison

Hazelcast	Azure Redis Cache
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.	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.
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	Enterprise-grade security; Flexible scaling; Improve application throughput and latency; Speed up applications with a distributed cache
Statistics
GitHub Stars 6.4K	GitHub Stars -
GitHub Forks 1.9K	GitHub Forks -
Stacks 427	Stacks 58
Followers 474	Followers 124
Votes 59	Votes 7
Pros & Cons
Pros 11 High Availibility 6 Distributed Locking 6 Distributed compute 5 Sharding 4 Load balancing Cons 4 License needed for SSL	Pros 4 Cache-cluster 3 Redis
Integrations
Java Spring	Spring Boot Java

What are some alternatives to Hazelcast, Azure Redis Cache?

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 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 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

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

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.

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

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

KeyDB

KeyDB is a fully open source database that aims to make use of all hardware resources. KeyDB makes it possible to breach boundaries often dictated by price and complexity.

LokiJS

LokiJS is a document oriented database written in javascript, published under MIT License. Its purpose is to store javascript objects as documents in a nosql fashion and retrieve them with a similar mechanism. Runs in node (including cordova/phonegap and node-webkit), nativescript and the browser.

BuntDB

BuntDB is a low-level, in-memory, key/value store in pure Go. It persists to disk, is ACID compliant, and uses locking for multiple readers and a single writer. It supports custom indexes and geospatial data. It's ideal for projects that need a dependable database and favor speed over data size.

Related Comparisons

Azure Redis Cache vs Hazelcast: What are the differences?

1. Scalability: Azure Redis Cache provides the ability to scale up or down based on the demand of the application, allowing users to easily handle varying workloads. On the other hand, Hazelcast offers both horizontal scaling, where additional nodes can be added to the cluster, and vertical scaling, where the size of individual nodes can be increased or decreased.
2. Data Persistence: Azure Redis Cache supports data persistence by offering options like RDB snapshots and AOF logs, which allow data to be stored even if the cache is restarted. Hazelcast also provides data persistence, but it does so through its built-in Map Store, which allows data to be stored in an external database or file system for durability.
3. Caching Strategies: Azure Redis Cache supports different caching strategies, such as LRU (Least Recently Used), LFU (Least Frequently Used), and custom eviction policies. Hazelcast, on the other hand, offers support for distributed caching with various eviction policies like LRU, LFU, and random eviction.
4. Integration with Microsoft Azure: Azure Redis Cache is a fully managed caching service provided by Microsoft Azure, allowing easy integration with other Azure services and providing features like high availability and automatic failover. In contrast, Hazelcast can be deployed on-premises or on any cloud platform, offering more flexibility in terms of deployment options.
5. Language Support: Azure Redis Cache provides support for multiple programming languages including .NET, Java, Node.js, Python, and more, making it accessible for developers using different technologies. Hazelcast also supports a wide range of programming languages, making it suitable for developers using different stacks and frameworks.
6. Security: Azure Redis Cache offers various security features, such as SSL/TLS encryption, Access Control Lists (ACLs), and Virtual Network Service Endpoints, ensuring confidentiality and restricting access to the cache. Hazelcast also provides security features like LDAP integration, SSL encryption, and network segregation to protect the cache and control access.

In summary, Azure Redis Cache and Hazelcast differ in terms of scalability, data persistence, caching strategies, integration with Microsoft Azure, language support, and security features.

Azure Redis Cache vs Hazelcast

Overview