DBMS > Ehcache vs. Microsoft Azure Table Storage vs. RDF4J vs. Sadas Engine

System Properties Comparison Ehcache vs. Microsoft Azure Table Storage vs. RDF4J vs. Sadas Engine

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

A Wide Column Store for rapid development using massive semi-structured datasets

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

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

Score	5.23
Rank	#68	Overall
	#8	Key-value stores

Score	4.92
Rank	#73	Overall
	#6	Wide column stores

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	0.03
Rank	#379	Overall
	#156	Relational DBMS

Website

www.ehcache.org

azure.microsoft.com/en-us/services/storage/tables

rdf4j.org

www.sadasengine.com

Technical documentation

www.ehcache.org/documentation

rdf4j.org/documentation

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Terracotta Inc, owned by Software AG

Microsoft

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

SADAS s.r.l.

Initial release

2009

2012

2004

2006

Current release

3.10.0, March 2022

8.0

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

free trial version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++

Server operating systems

All OS with a Java VM

hosted

Linux
OS X
Unix
Windows

AIX
Linux
Windows

Data scheme

schema-free

yes

RDF Schemas

yes

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

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC
Proprietary protocol

Supported programming languages

Java

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

Java
PHP
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

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

Implicit feature of the cloud service

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

optimistic locking

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

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

managed by 'Learn by Usage'

User concepts

Access control

Access rights based on private key authentication or shared access signatures

Access rights for users, groups and roles according to SQL-standard

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