DBMS > Ignite vs. MySQL vs. Splice Machine vs. TerminusDB vs. UniData,UniVerse

System Properties Comparison Ignite vs. MySQL vs. Splice Machine vs. TerminusDB vs. UniData,UniVerse

Editorial information provided by DB-Engines

Name

Description

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.

Widely used open source RDBMS

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

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

MultiValue database and application server with SQL mapping layer and meta database capabilities

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Graph DBMS

Multivalue DBMS

Secondary database models

Document store
Spatial DBMS

Document store
RDF store

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

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	3.16
Rank	#97	Overall
	#2	Multivalue DBMS

Website

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-unidata

Technical documentation

apacheignite.readme.io/docs

dev.mysql.com/doc

splicemachine.com/how-it-works

terminusdb.github.io/terminusdb/#

docs.rocketsoftware.com/bundle?cluster=true&labelkey=unidata&labelkey=prod_unidata

Developer

Apache Software Foundation

Oracle

since 2010, originally MySQL AB, then Sun

Splice Machine

DataChemist Ltd.

Rocket Software

Initial release

2015

1995

2014

2018

1985

Current release

Apache Ignite 2.6

8.4.0, April 2024

3.1, March 2021

11.0.0, January 2023

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

AGPL 3.0, commercial license available

Open Source

GPL V3

commercial

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.

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Implementation language

C++, Java, .Net

C and C++

Java

Prolog, Rust

Server operating systems

Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

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

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

yes

with proprietary extensions

yes

SQL-like query language (WOQL)

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
Native Spark Datasource
ODBC

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Java API

JPA
JDBC
ODBC
OLE DB
Proprietary protocol
RESTful HTTP API
SOAP-based API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

JavaScript
Python

.Net
Basic

U2 Basic
C
Java

Server-side scripts

Stored procedures

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

yes

proprietary syntax

yes

Java

yes

Triggers

yes (cache interceptors and events)

yes

U2 Basic

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Shared Nothhing Auto-Sharding, Columnar Partitioning

Graph Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Multi-source replication
Source-replica replication

Journaling Streams

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

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

configurable

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

Security Hooks for custom implementations

Users with fine-grained authorization concept

no user groups or roles

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

Role-based access control

Access rights according to SQL-standard and operating system based

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