DBMS > AnzoGraph DB vs. Badger vs. EXASOL vs. RDF4J vs. Riak KV

System Properties Comparison AnzoGraph DB vs. Badger vs. EXASOL vs. RDF4J vs. Riak KV

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

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

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

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

Distributed, fault tolerant key-value store

Primary database model

with links between data sets and object tags for the creation of secondary indexes

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

Score	0.22
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

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

Score	1.66
Rank	#138	Overall
	#64	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	3.84
Rank	#76	Overall
	#9	Key-value stores

Website

cambridgesemantics.com/anzograph

github.com/dgraph-io/badger

www.exasol.com

rdf4j.org

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

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

www.exasol.com/resources

rdf4j.org/documentation

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Cambridge Semantics

DGraph Labs

Exasol

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

OpenSource, formerly Basho Technologies

Initial release

2018

2017

2000

2004

2009

Current release

2.3, January 2021

3.2.0, December 2022

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache version 2, commercial enterprise edition

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

Erlang

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Unix
Windows

Linux
OS X

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

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

restricted

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

.Net
JDBC
ODBC
WebSocket

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API
Native Erlang Interface

Supported programming languages

C++
Java
Python

Java
Lua
Python
R

Java
PHP
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

yes

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

none

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

none

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

links between data sets can be stored

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.

yes

User concepts

Access control

Access rights for users and roles

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

yes, using Riak Security

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More resources

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