DBMS > Geode vs. Ignite vs. MySQL vs. Sphinx vs. ToroDB

System Properties Comparison Geode vs. Ignite vs. MySQL vs. Sphinx vs. ToroDB

Editorial information provided by DB-Engines

Name

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

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 search engine for searching in data from different sources, e.g. relational databases

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Key-value store

Key-value store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Search engine

Document store

Secondary database models

Document store
Spatial DBMS

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

Score	1.86
Rank	#134	Overall
	#24	Key-value stores

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

github.com/torodb/server

Technical documentation

geode.apache.org/docs

apacheignite.readme.io/docs

dev.mysql.com/doc

sphinxsearch.com/docs

Developer

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

Apache Software Foundation

Oracle

since 2010, originally MySQL AB, then Sun

Sphinx Technologies Inc.

8Kdata

Initial release

2002

2015

1995

2001

2016

Current release

1.1, February 2017

Apache Ignite 2.6

8.4.0, April 2024

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

Open Source

Apache 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL version 2, commercial licence available

Open Source

AGPL-V3

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

Java

C++, Java, .Net

C and C++

C++

Java

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, boolean, date, object_id

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

full-text index on all search fields

SQL

Support of SQL

SQL-like query language (OQL)

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

yes

with proprietary extensions

SQL-like query language (SphinxQL)

APIs and other access methods

Java Client API
Memcached protocol
RESTful HTTP API

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

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol

Supported programming languages

.Net
All JVM based languages
C++
Groovy
Java
Scala

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++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

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

yes

proprietary syntax

Triggers

yes

Cache Event Listeners

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes (replicated cache)

Multi-source replication
Source-replica replication

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

yes, on a single node

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

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

Access rights per client and object definable

Security Hooks for custom implementations

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

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