DBMS > GigaSpaces vs. Lovefield vs. OpenQM vs. OrientDB vs. RDF4J

System Properties Comparison GigaSpaces vs. Lovefield vs. OpenQM vs. OrientDB vs. RDF4J

Editorial information provided by DB-Engines

Name

Description

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Embeddable relational database for web apps written in pure JavaScript

QpenQM is a high-performance, self-tuning, multi-value DBMS

Multi-model DBMS (Document, Graph, Key/Value)

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

Primary database model

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Multivalue DBMS

Document store
Graph DBMS
Key-value store

RDF store

Secondary database models

Graph DBMS
Search engine

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

Score	0.91
Rank	#197	Overall
	#33	Document stores
	#7	Object oriented DBMS

Score	0.22
Rank	#306	Overall
	#138	Relational DBMS

Score	0.28
Rank	#291	Overall
	#10	Multivalue DBMS

Score	3.02
Rank	#88	Overall
	#16	Document stores
	#6	Graph DBMS
	#12	Key-value stores

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

www.gigaspaces.com

google.github.io/lovefield

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

orientdb.org

rdf4j.org

Technical documentation

docs.gigaspaces.com/latest/landing.html

github.com/google/lovefield/blob/master/docs/spec_index.md

www.orientdb.com/docs/last/index.html

rdf4j.org/documentation

Developer

Gigaspaces Technologies

Google

Rocket Software, originally Martin Phillips

OrientDB LTD; CallidusCloud; SAP

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

Initial release

2000

2014

1993

2010

2004

Current release

15.5, September 2020

2.1.12, February 2017

3.4-12

3.2.29, March 2024

License

Commercial or Open Source

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache 2.0

Open Source

GPLv2, extended commercial license available

Open Source

Apache version 2

Open Source

Eclipse Distribution License (EDL), v1.0.

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++, .Net

JavaScript

Java

Server operating systems

Linux
macOS
Solaris
Windows

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

All OS with a Java JDK (>= JDK 6)

Linux
OS X
Unix
Windows

Data scheme

schema-free

yes

with some exceptions

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

yes

RDF Schemas

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-99 for query and DML statements

SQL-like query language

via JavaScript builder pattern

SQL-like query language, no joins

APIs and other access methods

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

.Net
C++
Java
Python
Scala

JavaScript

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Java, Javascript

yes

Triggers

yes, event driven architecture

Using read-only observers

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

none

yes

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

Transaction concepts

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

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

in-memory storage is supported as well

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

Role-based access control

Access rights can be defined down to the item level

Access rights for users and roles; record level security configurable

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More resources

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