DBMS > H2 vs. Linter vs. RDFox vs. XTDB

System Properties Comparison H2 vs. Linter vs. RDFox vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

RDBMS for high security requirements

High performance knowledge graph and semantic reasoning engine

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS

Graph DBMS
RDF store

Document store

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	0.29
Rank	#300	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.h2database.com

linter.ru

www.oxfordsemantic.tech

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

www.h2database.com/html/main.html

docs.oxfordsemantic.tech

www.xtdb.com/docs

Developer

Thomas Mueller

relex.ru

Oxford Semantic Technologies

Juxt Ltd.

Initial release

2005

1990

2017

2019

Current release

2.2.220, July 2023

6.0, Septermber 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Open Source

MIT License

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 and C++

C++

Clojure

Server operating systems

All OS with a Java VM

AIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows

Linux
macOS
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

RDF schemas

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)

RESTful HTTP API
SPARQL 1.1

HTTP REST
JDBC

Supported programming languages

Java

C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl

C
Java

Clojure
Java

Server-side scripts

Stored procedures

Java Stored Procedures and User-Defined Functions

yes

proprietary syntax with the possibility to convert from PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

Source-replica replication

replication via a shared file system

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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

Roles, resources, and access types

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More resources

Recent citations in the news

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