Hazelcast vs Jboss Data Grid

Overview

Hazelcast

Stacks427

Followers474

Votes59

GitHub Stars6.4K

Forks1.9K

Jboss Data Grid

Stacks1

Followers10

Votes0

Hazelcast vs Jboss Data Grid: What are the differences?

Introduction

Hazelcast and Jboss Data Grid are two popular distributed caching solutions used for storing and managing large volumes of data across a cluster of machines. While both offer similar functionalities, there are several key differences between them.

Data Model: Hazelcast is a distributed in-memory data grid that provides a key-value store, whereas Jboss Data Grid is a distributed data grid that focuses on providing a distributed cache with advanced data grid capabilities such as indexing, querying, and transactional support.
Concurrency Control: Hazelcast uses optimistic concurrency control, allowing concurrent access to data with the assumption that conflicts are rare. On the other hand, Jboss Data Grid offers both optimistic and pessimistic concurrency control, allowing the application to choose between different concurrency strategies as per their requirements.
Data Partitioning: Hazelcast uses automatic data partitioning, where the data is automatically distributed across multiple nodes in the cluster based on hash values of keys. Jboss Data Grid, on the other hand, provides flexible data partitioning options, allowing custom partitioning strategies based on application-defined rules.
Eventual Consistency: Hazelcast provides strong eventual consistency guarantees, ensuring that all updates are propagated to all replicas eventually. Jboss Data Grid offers configurable consistency levels, allowing applications to choose between stronger consistency guarantees or higher performance.
Integration with Existing Infrastructure: Jboss Data Grid is closely integrated with other JBoss middleware components, making it a preferred choice for applications built on the JBoss platform. Hazelcast, being a standalone solution, provides more flexibility in terms of integration with various middleware and application stacks.
Management and Monitoring: Jboss Data Grid provides a rich set of management and monitoring tools, including a web-based management console, CLI tools, and integration with other monitoring frameworks. Hazelcast also offers management and monitoring capabilities, but with a simpler and lighter-weight approach.

In summary, Hazelcast and Jboss Data Grid are both powerful distributed caching solutions, but differ in terms of data model, concurrency control, data partitioning, consistency guarantees, integration with existing infrastructure, and management and monitoring capabilities.

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CLI (Node.js)

Manual

Detailed Comparison

Hazelcast	Jboss Data Grid
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.	Red Hat is the world’s leading provider of open source solutions, using a community-powered approach to provide reliable and high-performing cloud, virtualization, storage, Linux, and middleware technologies. Red Hat also offers award-winning support, training, and consulting services. Red Hat is an S&P 500 company with more than 80 offices spanning the globe, empowering its customers’ businesses.
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 6.4K	GitHub Stars -
GitHub Forks 1.9K	GitHub Forks -
Stacks 427	Stacks 1
Followers 474	Followers 10
Votes 59	Votes 0
Pros & Cons
Pros 11 High Availibility 6 Distributed compute 6 Distributed Locking 5 Sharding 4 Load balancing Cons 4 License needed for SSL	No community feedback yet
Integrations
Java Spring	No integrations available

What are some alternatives to Hazelcast, Jboss Data Grid?

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

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.

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.

Related Comparisons

Hazelcast vs Jboss Data Grid: What are the differences?

Introduction

Data Model: Hazelcast is a distributed in-memory data grid that provides a key-value store, whereas Jboss Data Grid is a distributed data grid that focuses on providing a distributed cache with advanced data grid capabilities such as indexing, querying, and transactional support.
Concurrency Control: Hazelcast uses optimistic concurrency control, allowing concurrent access to data with the assumption that conflicts are rare. On the other hand, Jboss Data Grid offers both optimistic and pessimistic concurrency control, allowing the application to choose between different concurrency strategies as per their requirements.
Data Partitioning: Hazelcast uses automatic data partitioning, where the data is automatically distributed across multiple nodes in the cluster based on hash values of keys. Jboss Data Grid, on the other hand, provides flexible data partitioning options, allowing custom partitioning strategies based on application-defined rules.
Eventual Consistency: Hazelcast provides strong eventual consistency guarantees, ensuring that all updates are propagated to all replicas eventually. Jboss Data Grid offers configurable consistency levels, allowing applications to choose between stronger consistency guarantees or higher performance.
Integration with Existing Infrastructure: Jboss Data Grid is closely integrated with other JBoss middleware components, making it a preferred choice for applications built on the JBoss platform. Hazelcast, being a standalone solution, provides more flexibility in terms of integration with various middleware and application stacks.
Management and Monitoring: Jboss Data Grid provides a rich set of management and monitoring tools, including a web-based management console, CLI tools, and integration with other monitoring frameworks. Hazelcast also offers management and monitoring capabilities, but with a simpler and lighter-weight approach.

Hazelcast vs Jboss Data Grid

Overview

Hazelcast vs Jboss Data Grid: What are the differences?