DBMS > Atos Standard Common Repository vs. JanusGraph vs. Oracle NoSQL vs. SpatiaLite

System Properties Comparison Atos Standard Common Repository vs. JanusGraph vs. Oracle NoSQL vs. SpatiaLite

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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

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

A Graph DBMS optimized for distributed clusters

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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Spatial extension of SQLite

Primary database model

Document store
Key-value store

Graph DBMS

Document store
Key-value store
Relational DBMS

Spatial DBMS

Secondary database models

Relational DBMS

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

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	1.60
Rank	#149	Overall
	#3	Spatial DBMS

Website

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

janusgraph.org

www.oracle.com/database/nosql/technologies/nosql

www.gaia-gis.it/fossil/libspatialite/index

Technical documentation

docs.janusgraph.org

docs.oracle.com/en/database/other-databases/nosql-database/index.html

www.gaia-gis.it/gaia-sins/spatialite_topics.html

Developer

Atos Convergence Creators

Linux Foundation; originally developed as Titan by Aurelius

Oracle

Alessandro Furieri

Initial release

2016

2017

2011

2008

Current release

1703

0.6.3, February 2023

23.3, December 2023

5.0.0, August 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

MPL 1.1, GPL v2.0 or LGPL v2.1

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
Unix
Windows

Linux
Solaris SPARC/x86

server-less

Data scheme

Schema and schema-less with LDAP views

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

optional

yes

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

SQL-like DML and DDL statements

yes

APIs and other access methods

LDAP

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

RESTful HTTP API

Supported programming languages

All languages with LDAP bindings

Clojure
Java
Python

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

yes

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

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

configurable

ACID within a storage node (=shard)

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

off heap cache

yes

User concepts

Access control

LDAP bind authentication

User authentification and security via Rexster Graph Server

Access rights for users and roles

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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