DBMS > H2 vs. Hazelcast vs. Ignite

System Properties Comparison H2 vs. Hazelcast vs. Ignite

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A widely adopted in-memory data grid

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

Primary database model

Relational DBMS

Key-value store

Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

Document store

JSON support with IMDG 3.12

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	9.01
Rank	#52	Overall
	#33	Relational DBMS

Score	7.92
Rank	#57	Overall
	#6	Key-value stores

Score	5.16
Rank	#83	Overall
	#10	Key-value stores
	#44	Relational DBMS

Website

www.h2database.com

hazelcast.com

ignite.apache.org

Technical documentation

www.h2database.com/html/main.html

hazelcast.org/imdg/docs

apacheignite.readme.io/docs

Developer

Thomas Mueller

Hazelcast

Apache Software Foundation

Initial release

2005

2008

2015

Current release

2.1.214, June 2022

5.2.2, February 2023

Apache Ignite 2.6

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++, Java, .Net

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

Java

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

Event Listeners, Executor Services

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

Events

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

Replicated Map

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role-based access control

Security Hooks for custom implementations

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More resources

Recent citations in the news

Hazelcast to Highlight How to Accelerate Measurable Business ...
16 May 2023, GlobeNewswire

Open Source Provides Path to Real-Time Stream Processing
8 May 2023, Datanami

Hazelcast Recognized as Leader in GigaOm Radar Report for ...
24 April 2023, MarTech Series

Hazelcast CEO: Automation Rules The Real-Time Economy
10 December 2022, Forbes

Hazelcast Aims to Democratize Real-Time Data with Serverless
3 October 2022, The New Stack

provided by Google News

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

Fire up big data processing with Apache Ignite
27 October 2016, InfoWorld

Merge branch 'IGNITE-15629' into IGNITE-15629-cleanup · apache/ignite@8f7402e
2 June 2023, github.com

GridGain / Apache Ignite Training
28 March 2023, gridgain.com

IGNITE-15629 Cache find_garbage command implemented · apache/ignite@62f123c
2 June 2023, github.com

provided by Google News

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