DBMS > AnzoGraph DB vs. Badger vs. mSQL vs. OrigoDB vs. RDF4J

System Properties Comparison AnzoGraph DB vs. Badger vs. mSQL vs. OrigoDB vs. RDF4J

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.

mSQL (Mini SQL) is a simple and lightweight RDBMS

A fully ACID in-memory object graph database

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

Primary database model

Graph DBMS
RDF store

Key-value store

Relational DBMS

Document store
Object oriented DBMS

RDF store

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

cambridgesemantics.com/anzograph

github.com/dgraph-io/badger

hughestech.com.au/products/msql

origodb.com

rdf4j.org

Technical documentation

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

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

origodb.com/docs

rdf4j.org/documentation

Developer

Cambridge Semantics

DGraph Labs

Hughes Technologies

Robert Friberg et al

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

Initial release

2018

2017

1994

2009

under the name LiveDB

2004

Current release

2.3, January 2021

4.4, October 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

Apache 2.0

commercial

free licenses can be provided

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

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

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

APIs and other access methods

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

JDBC
ODBC

.NET Client API
HTTP API
LINQ

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

C++
Java
Python

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

none

Foreign keys

Referential integrity

not needed in graphs

depending on model

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

Write ahead log

yes

in-memory storage is supported as well

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

Role based authorization

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More resources

Recent citations in the news

AnzoGraph review: A graph database for deep analytics
15 April 2019, InfoWorld

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
23 January 2020, Solutions Review

AnzoGraph: A W3C Standards-Based Graph Database | by Jo Stichbury
8 February 2019, Towards Data Science

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

Is The Enterprise Knowledge Graph Finally Going To Make All Data Usable?
19 September 2018, Forbes

provided by Google News

Higher Education PS rules out ghost students before PAC
29 November 2018, diggers.news

provided by Google News

GraphDB Goes Open Source
27 January 2020, iProgrammer

provided by Google News

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