DBMS > H2 vs. Ignite vs. searchxml vs. Splice Machine

System Properties Comparison H2 vs. Ignite vs. searchxml vs. Splice Machine

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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.

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.

DBMS for structured and unstructured content wrapped with an application server

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Native XML DBMS
Search engine

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	3.64
Rank	#89	Overall
	#13	Key-value stores
	#48	Relational DBMS

Score	0.01
Rank	#386	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Website

www.h2database.com

ignite.apache.org

www.searchxml.net/category/products

splicemachine.com

Technical documentation

www.h2database.com/html/main.html

apacheignite.readme.io/docs

www.searchxml.net/support/handouts

splicemachine.com/how-it-works

Developer

Thomas Mueller

Apache Software Foundation

informationpartners gmbh

Splice Machine

Initial release

2005

2015

2014

Current release

2.2.220, July 2023

Apache Ignite 2.6

1.0

3.1, March 2021

License

Commercial or Open Source

Open Source

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

Open Source

Apache 2.0

commercial

Open Source

AGPL 3.0, commercial license available

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

C++

Java

Server operating systems

All OS with a Java VM

Linux
OS X
Solaris
Windows

Windows

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

Secondary indexes

yes

SQL

Support of SQL

yes

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

yes

APIs and other access methods

JDBC
ODBC

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

RESTful HTTP API
WebDAV
XQuery
XSLT

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Java

C#
C++
Java
PHP
Python
Ruby
Scala

C++

most other programming languages supported via APIs

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

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

yes

on the application server

yes

Java

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

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 cache)

yes

sychronisation to multiple collections

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

multiple readers, single writer

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

yes, multi-version concurrency control (MVCC)

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

Security Hooks for custom implementations

Domain, group and role-based access control at the document level and for application services

Access rights for users, groups and roles according to SQL-standard

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