DBMS > AnzoGraph DB vs. Atos Standard Common Repository vs. NuoDB

System Properties Comparison AnzoGraph DB vs. Atos Standard Common Repository vs. NuoDB

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Editorial information provided by DB-Engines

Name

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

Description

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

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

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Primary database model

Graph DBMS
RDF store

Document store
Key-value store

Relational DBMS

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	0.89
Rank	#198	Overall
	#92	Relational DBMS

Website

cambridgesemantics.com/anzograph

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

www.3ds.com/nuodb-distributed-sql-database

Technical documentation

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

doc.nuodb.com

Developer

Cambridge Semantics

Atos Convergence Creators

Dassault Systèmes

originally NuoDB, Inc.

Initial release

2018

2016

2013

Current release

2.3, January 2021

1703

License

Commercial or Open Source

commercial

free trial version available

commercial

limited edition free

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

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

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

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

LDAP

ADO.NET
JDBC
ODBC

Supported programming languages

C++
Java
Python

All languages with LDAP bindings

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

Server-side scripts

Stored procedures

user defined functions and aggregates

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

cell division

data is dynamically stored/cached on the nodes where it is read/written

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

Managed transparently by NuoDB

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

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

MVCC

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

Temporary table

User concepts

Access control

Access rights for users and roles

LDAP bind authentication

Standard SQL roles/ privileges, Administrative Users

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More resources

DB-Engines blog posts

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Recent citations in the news

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

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8 February 2019, Towards Data Science

Back to the future: Does graph database success hang on query language?
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