DBMS > Badger vs. Linter vs. Oracle Rdb vs. RDF4J vs. TigerGraph

System Properties Comparison Badger vs. Linter vs. Oracle Rdb vs. RDF4J vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

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

RDBMS for high security requirements

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

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Secondary database models

Spatial DBMS

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

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

Score	0.12
Rank	#350	Overall
	#152	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

github.com/dgraph-io/badger

linter.ru

www.oracle.com/database/technologies/related/rdb.html

rdf4j.org

www.tigergraph.com

Technical documentation

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

www.oracle.com/database/technologies/related/rdb-doc.html

rdf4j.org/documentation

docs.tigergraph.com

Developer

DGraph Labs

relex.ru

Oracle, originally developed by Digital Equipment Corporation (DEC)

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

Initial release

2017

1990

1984

2004

2017

Current release

7.4.1.1, 2021

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

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

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

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

HP Open VMS

Linux
OS X
Unix
Windows

Linux

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, 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

SQL-like query language (GSQL)

APIs and other access methods

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

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

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

Java
PHP
Python

C++
Java

Server-side scripts

Stored procedures

yes

proprietary syntax with the possibility to convert from PL/SQL

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

yes, on a single node

ACID

Isolation support depends on the API used

ACID

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

Role-based access control

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