DBMS > EsgynDB vs. MaxDB vs. Oracle Coherence vs. RDF4J

System Properties Comparison EsgynDB vs. MaxDB vs. Oracle Coherence vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A robust and reliable RDBMS optimized to run all major SAP solutions

Oracles in-memory data grid solution

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

Primary database model

Relational DBMS

Key-value store

RDF store

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

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	2.15
Rank	#115	Overall
	#55	Relational DBMS

Score	1.90
Rank	#127	Overall
	#21	Key-value stores

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

www.esgyn.cn

maxdb.sap.com

www.oracle.com/java/coherence

rdf4j.org

Technical documentation

maxdb.sap.com/documentation

docs.oracle.com/en/middleware/standalone/coherence

rdf4j.org/documentation

Developer

Esgyn

SAP, acquired from Software AG (Adabas-D) in 1997

Oracle

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

Initial release

2015

1984

2007

2004

Current release

7.9.10.12, February 2024

14.1, August 2023

License

Commercial or Open Source

commercial

Limited community edition free

commercial

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

C++, Java

C++

Java

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows

All OS with a Java VM

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
WebDAV

JCache
JPA
RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

.Net
C#
Java
Perl
PHP
Python

.Net
C++
Java

Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Source-replica replication

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

authentification to access the cache via certificates or http basic authentication

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