DBMS > Graph Engine vs. Greenplum vs. HyperSQL vs. RDF4J

System Properties Comparison Graph Engine vs. Greenplum vs. HyperSQL vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Primary database model

Graph DBMS
Key-value store

Relational DBMS

RDF store

Secondary database models

Document store
Spatial DBMS

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

Score	0.67
Rank	#232	Overall
	#21	Graph DBMS
	#34	Key-value stores

Score	8.08
Rank	#48	Overall
	#31	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

Technical documentation

www.graphengine.io/docs/manual

docs.greenplum.org

hsqldb.org/web/hsqlDocsFrame.html

rdf4j.org/documentation

Developer

Microsoft

Pivotal Software Inc.

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

Initial release

2010

2005

2001

2004

Current release

7.0.0, September 2023

2.7.2, June 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

based on BSD license

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

.NET and C

Java

Server operating systems

.NET

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
OS X
Unix
Windows

Data scheme

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.

yes

since Version 4.2

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C#
C++
F#
Visual Basic

C
Java
Perl
Python
R

All languages supporting JDBC/ODBC
Java

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Java, SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

User concepts

Access control

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

Trinity
30 October 2010, Microsoft

Open source Microsoft Graph Engine takes on Neo4j
13 February 2017, InfoWorld

IBM releases Graph, a service that can outperform SQL databases
27 July 2016, GeekWire

Aerospike Is Now a Graph Database, Too
21 June 2023, Datanami

The graph analytics landscape 2019 - DataScienceCentral.com
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1. Introducing the Greenplum Database - Data Warehousing with Greenplum [Book]
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RSA: EMC integrates Hadoop with Greenplum database
26 February 2013, DatacenterDynamics

Greenplum 6 ventures outside the analytic box | ZDNET
19 March 2019, ZDNet

Greenplum 6 review: Jack of all trades, master of some
7 November 2019, InfoWorld

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HyperSQL DataBase flaw leaves library vulnerable to RCE
24 October 2022, The Daily Swig

Introduction to JDBC with HSQLDB tutorial
14 November 2022, TheServerSide.com

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GraphDB Goes Open Source
27 January 2020, iProgrammer

Ontotext's GraphDB 8.10 Makes Knowledge Graph Experience Faster and Richer
13 June 2019, Markets Insider

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