DBMS > Ehcache vs. EsgynDB vs. Graph Engine vs. RDF4J

System Properties Comparison Ehcache vs. EsgynDB vs. Graph Engine vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

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

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

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

Primary database model

Key-value store

Relational DBMS

Graph DBMS
Key-value store

RDF store

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

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

Technical documentation

www.ehcache.org/documentation

www.graphengine.io/docs/manual

rdf4j.org/documentation

Developer

Terracotta Inc, owned by Software AG

Esgyn

Microsoft

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

Initial release

2009

2015

2010

2004

Current release

3.10.0, March 2022

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

MIT 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

Java

C++, Java

.NET and C

Java

Server operating systems

All OS with a Java VM

Linux

.NET

Linux
OS X
Unix
Windows

Data scheme

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

JCache

ADO.NET
JDBC
ODBC

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

Java

All languages supporting JDBC/ODBC/ADO.Net

C#
C++
F#
Visual Basic

Java
PHP
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Multi-source replication between multi datacenters

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

supports JTA and can work as an XA resource

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

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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