DBMS > AgensGraph vs. Blazegraph vs. IBM Cloudant vs. JanusGraph vs. MariaDB

System Properties Comparison AgensGraph vs. Blazegraph vs. IBM Cloudant vs. JanusGraph vs. MariaDB

Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

Database as a Service offering based on Apache CouchDB

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

Primary database model

Graph DBMS
Relational DBMS

Secondary database models

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

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

Score	0.16
Rank	#333	Overall
	#30	Graph DBMS
	#146	Relational DBMS

Score	0.77
Rank	#222	Overall
	#20	Graph DBMS
	#8	RDF stores

Score	2.73
Rank	#108	Overall
	#20	Document stores

Score	1.91
Rank	#135	Overall
	#12	Graph DBMS

Score	93.81
Rank	#13	Overall
	#9	Relational DBMS

Website

bitnine.net/agensgraph

blazegraph.com

www.ibm.com/products/cloudant

janusgraph.org

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

Technical documentation

bitnine.net/documentation

wiki.blazegraph.com

cloud.ibm.com/docs/Cloudant

docs.janusgraph.org

mariadb.com/kb/en/library

Developer

Bitnine Global Inc.

Blazegraph

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Linux Foundation; originally developed as Titan by Aurelius

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Initial release

2016

2006

2010

2017

2009

Fork of MySQL, which was first released in 1995

Current release

2.1, December 2018

2.1.5, March 2019

0.6.3, February 2023

11.3.2, February 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

extended commercial license available

commercial

Open Source

Apache 2.0

Open Source

GPL version 2, commercial enterprise subscription available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Erlang

Java

C and C++

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Unix
Windows

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

Data scheme

depending on used data model

schema-free

yes

Dynamic columns are supported

Typing

predefined data types such as float or date

yes

RDF literal types

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

Secondary indexes

yes

SQL

Support of SQL

yes

SPARQL is used as query language

yes

with proprietary extensions

APIs and other access methods

Cypher Query Language
JDBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

RESTful HTTP/JSON API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
Java
JavaScript
Python

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C#
Java
JavaScript
Objective-C
PHP
Ruby

Clojure
Java
Python

Ada
C
C#
C++
D
Eiffel
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

View functions (Map-Reduce) in JavaScript

yes

PL/SQL compatibility added with version 10.3

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

several options for horizontal partitioning and Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication
Source-replica replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

Relationships in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

atomic operations within a document possible

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

not for in-memory storage engine

In-memory capabilities

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

yes

with MEMORY storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

Security and Authentication via Web Application Container (Tomcat, Jetty)

Access rights for users can be defined per database

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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