DBMS > Badger vs. GraphDB vs. RDF4J vs. VoltDB

System Properties Comparison Badger vs. GraphDB vs. RDF4J vs. VoltDB

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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.

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

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

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	2.76
Rank	#99	Overall
	#8	Graph DBMS
	#4	RDF stores

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	1.38
Rank	#156	Overall
	#72	Relational DBMS

Website

github.com/dgraph-io/badger

www.ontotext.com

rdf4j.org

www.voltdb.com

Technical documentation

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

graphdb.ontotext.com/documentation

rdf4j.org/documentation

docs.voltdb.com

Social network pages

Developer

DGraph Labs

Ontotext

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

VoltDB Inc.

Initial release

2017

2000

2004

2010

Current release

10.4, October 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Java, C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM
Linux
OS X
Windows

Linux
OS X
Unix
Windows

Linux
OS X

for development

Data scheme

schema-free

schema-free and OWL/RDFS-schema support; RDF shapes

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, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

SQL

Support of SQL

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

yes

only a subset of SQL 99

APIs and other access methods

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Java
PHP
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

well-defined plugin interfaces; JavaScript server-side extensibility

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Foreign keys

Referential integrity

yes

Constraint checking

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Isolation support depends on the API used

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes

Snapshots and command logging

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

GraphDB in Action: Using Semantics To Push The Envelope Of Software Engineering, Machine Learning, and E-Health Domains
11 September 2024

Accelerating End-to-end Knowledge Graph Solutions with Ontotext’s LinkedLifeData Inventory: The Case of Target Discovery
30 August 2024

Using Entity Linking to Turn Your Graph into a Knowledge Graph
23 August 2024

Considerations to Creating a Graph Center of Excellence: 5 Elements to Ensure Success
22 August 2024

The Power of Knowledge Graphs – A Chat with Perfect Memory and Ontotext
16 August 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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