DBMS > Geode vs. GridGain vs. OrigoDB vs. RDF4J vs. STSdb

System Properties Comparison Geode vs. GridGain vs. OrigoDB vs. RDF4J 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

A fully ACID in-memory object graph database

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

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

Document store
Object oriented DBMS

RDF store

Key-value store

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	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

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

Website

github.com/STSSoft/STSdb4

Technical documentation

geode.apache.org/docs

www.gridgain.com/docs/index.html

origodb.com/docs

rdf4j.org/documentation

Developer

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

GridGain Systems, Inc.

Robert Friberg et al

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

STS Soft SC

Initial release

2002

2007

2009

under the name LiveDB

2004

2011

Current release

1.1, February 2017

GridGain 8.5.1

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GPLv2, 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

Java, C++, .Net

Java

Server operating systems

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Solaris
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Windows

Data scheme

schema-free

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (OQL)

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

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

.NET Client API
HTTP API
LINQ

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

.NET Client API

Supported programming languages

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

C#
C++
Java
PHP
Python
Ruby
Scala

.Net

Java
PHP
Python

C#
Java

Server-side scripts

Stored procedures

user defined functions

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

yes

Triggers

yes

Cache Event Listeners

yes (cache interceptors and events)

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes (replicated cache)

Source-replica replication

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

depending on model

Transaction concepts

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

yes, on a single node

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

in-memory storage is supported as well

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

Role based authorization

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