DBMS > Ehcache vs. RDF4J vs. Sadas Engine vs. Splice Machine

System Properties Comparison Ehcache vs. RDF4J vs. Sadas Engine vs. Splice Machine

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Key-value store

RDF store

Relational DBMS

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

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

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

Technical documentation

www.ehcache.org/documentation

rdf4j.org/documentation

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

splicemachine.com/how-it-works

Developer

Terracotta Inc, owned by Software AG

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

SADAS s.r.l.

Splice Machine

Initial release

2009

2004

2006

2014

Current release

3.10.0, March 2022

8.0

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

free trial version available

Open Source

AGPL 3.0, commercial license available

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

Server operating systems

All OS with a Java VM

Linux
OS X
Unix
Windows

AIX
Linux
Windows

Linux
OS X
Solaris
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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC
Proprietary protocol

JDBC
Native Spark Datasource
ODBC

Supported programming languages

Java

Java
PHP
Python

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

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

Java

Triggers

yes

Cache Event Listeners

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

none

horizontal partitioning

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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'

yes

User concepts

Access control

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

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