DBMS > Atos Standard Common Repository vs. Coveo vs. JanusGraph vs. Valentina Server

System Properties Comparison Atos Standard Common Repository vs. Coveo vs. JanusGraph vs. Valentina Server

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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

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

A Graph DBMS optimized for distributed clusters

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

Object-relational database and reports server

Primary database model

Document store
Key-value store

Search engine

Graph DBMS

Relational DBMS

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

Score	2.28
Rank	#114	Overall
	#11	Search engines

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.17
Rank	#327	Overall
	#145	Relational DBMS

Website

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

www.coveo.com

janusgraph.org

www.valentina-db.net

Technical documentation

docs.coveo.com

docs.janusgraph.org

valentina-db.com/docs/dokuwiki/v5/doku.php

Developer

Atos Convergence Creators

Coveo

Linux Foundation; originally developed as Titan by Aurelius

Paradigma Software

Initial release

2016

2012

2017

1999

Current release

1703

0.6.3, February 2023

5.7.5

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

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

Server operating systems

Linux

hosted

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

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

yes

APIs and other access methods

LDAP

RESTful HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

ODBC

Supported programming languages

All languages with LDAP bindings

C#
Java
JavaScript
Python

Clojure
Java
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

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)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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 or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency
Immediate Consistency

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

yes

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

granular access controls, API key management, content filters

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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