DBMS > Badger vs. Citus vs. RDF4J vs. SpaceTime

System Properties Comparison Badger vs. Citus vs. RDF4J vs. SpaceTime

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Secondary database models

Document store

Relational DBMS

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	0.03
Rank	#392	Overall
	#8	Spatial DBMS

Website

github.com/dgraph-io/badger

www.citusdata.com

rdf4j.org

www.mireo.com/spacetime

Technical documentation

godoc.org/github.com/dgraph-io/badger

docs.citusdata.com

rdf4j.org/documentation

Developer

DGraph Labs

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

Mireo

Initial release

2017

2010

2004

2020

Current release

8.1, December 2018

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

AGPL, commercial license also available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Unix
Windows

Linux

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.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

A subset of ANSI SQL is implemented

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

RESTful HTTP API

Supported programming languages

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java
PHP
Python

C#
C++
Python

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

other methods possible by using 3rd party extensions

none

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

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.

User concepts

Access control

fine grained access rights according to SQL-standard

yes

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