DBMS > Atos Standard Common Repository vs. Blazegraph vs. JanusGraph vs. Prometheus vs. TigerGraph

System Properties Comparison Atos Standard Common Repository vs. Blazegraph vs. JanusGraph vs. Prometheus vs. TigerGraph

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

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

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

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

A Graph DBMS optimized for distributed clusters

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

Open-source Time Series DBMS and monitoring system

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

Primary database model

Document store
Key-value store

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

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

Score	1.91
Rank	#135	Overall
	#12	Graph DBMS

Score	7.92
Rank	#51	Overall
	#2	Time Series DBMS

Score	1.83
Rank	#141	Overall
	#13	Graph DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

Technical documentation

Developer

Atos Convergence Creators

Blazegraph

Linux Foundation; originally developed as Titan by Aurelius

Initial release

2016

2006

2017

2015

2017

Current release

1703

2.1.5, March 2019

0.6.3, February 2023

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

Open Source

Apache 2.0

Open Source

Apache 2.0

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

Java

C++

Server operating systems

Linux

Linux
OS X
Windows

Linux
OS X
Unix
Windows

Linux
Windows

Linux

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

Typing

predefined data types such as float or date

optional

yes

RDF literal types

yes

Numeric data only

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

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

SPARQL is used as query language

SQL-like query language (GSQL)

APIs and other access methods

LDAP

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

RESTful HTTP/JSON API

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

Supported programming languages

All languages with LDAP bindings

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

Clojure
Java
Python

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

yes

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by Federation

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

Relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

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

LDAP bind authentication

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

User authentification and security via Rexster Graph Server

Role-based access control

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More resources

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