DBMS > Geode vs. GridGain vs. MySQL vs. SpaceTime vs. STSdb

System Properties Comparison Geode vs. GridGain vs. MySQL vs. SpaceTime vs. STSdb

Editorial information provided by DB-Engines

Name

Description

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

GridGain is an in-memory computing platform, built on Apache Ignite

Widely used open source RDBMS

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Key-value store

Key-value store
Relational DBMS

Relational DBMS

Key/Value like access via memcached API

Spatial DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

geode.apache.org

www.gridgain.com

www.mysql.com

www.mireo.com/spacetime

github.com/STSSoft/STSdb4

Technical documentation

geode.apache.org/docs

www.gridgain.com/docs/index.html

dev.mysql.com/doc

Developer

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

GridGain Systems, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Mireo

STS Soft SC

Initial release

2002

2007

1995

2020

2011

Current release

1.1, February 2017

GridGain 8.5.1

8.4.0, April 2024

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Open Source

GPLv2, commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Java

Java, C++, .Net

C and C++

C++

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

Linux

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

SQL-like query language (OQL)

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

yes

with proprietary extensions

A subset of ANSI SQL is implemented

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

RESTful HTTP API

.NET Client API

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#
C++
Python

C#
Java

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

Fixed-grid hypercubes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes (replicated cache)

Multi-source replication
Source-replica replication

Real-time block device replication (DRBD)

none

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

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

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

yes

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