DBMS > Machbase Neo vs. Oracle Coherence vs. RDF4J vs. SwayDB

System Properties Comparison Machbase Neo vs. Oracle Coherence vs. RDF4J vs. SwayDB

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Editorial information provided by DB-Engines

Name

Description

TimeSeries DBMS for AIoT and BigData

Oracles in-memory data grid solution

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

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

Score	0.22
Rank	#324	Overall
	#29	Time Series DBMS

Score	2.02
Rank	#131	Overall
	#22	Key-value stores

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	0.04
Rank	#373	Overall
	#57	Key-value stores

Website

machbase.com

www.oracle.com/java/coherence

rdf4j.org

swaydb.simer.au

Technical documentation

machbase.com/dbms

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

rdf4j.org/documentation

Developer

Machbase

Oracle

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

Simer Plaha

Initial release

2013

2007

2004

2018

Current release

V8.0, August 2023

14.1, August 2023

License

Commercial or Open Source

commercial

free test version available

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

GNU Affero GPL V3.0

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

Scala

Server operating systems

Linux
macOS
Windows

All OS with a Java VM

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

RDF Schemas

schema-free

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

SQL-like query language

APIs and other access methods

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

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

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

.Net
C++
Java

Java
PHP
Python

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes, with selectable consistency level

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

configurable

ACID

Isolation support depends on the API used

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

volatile and lookup table

yes

User concepts

Access control

simple password-based access control

authentification to access the cache via certificates or http basic authentication

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