DBMS > EXASOL vs. MonetDB vs. RDF4J vs. RocksDB vs. SwayDB

System Properties Comparison EXASOL vs. MonetDB vs. RDF4J vs. RocksDB vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

A relational database management system that stores data in columns

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

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Primary database model

Relational DBMS

RDF store

Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

Technical documentation

www.exasol.com/resources

www.monetdb.org/Documentation

rdf4j.org/documentation

github.com/facebook/rocksdb/wiki

Developer

Exasol

MonetDB BV

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

Facebook, Inc.

Simer Plaha

Initial release

2000

2004

2013

2018

Current release

Dec2023 (11.49), December 2023

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

BSD

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

C++

Scala

Server operating systems

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Linux

Data scheme

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

yes

SQL 2003 with some extensions

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

C++ API
Java API

Supported programming languages

Java
Lua
Python
R

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Java
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

yes, in SQL, C, R

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Isolation support depends on the API used

yes

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

User concepts

Access control

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

fine grained access rights according to SQL-standard

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