DBMS > Atos Standard Common Repository vs. Coveo vs. GeoSpock vs. RDF4J

System Properties Comparison Atos Standard Common Repository vs. Coveo vs. GeoSpock vs. RDF4J

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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.

GeoSpock seems to be discontinued. Therefore it will be excluded 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

Spatial and temporal data processing engine for extreme data scale

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Document store
Key-value store

Search engine

Relational DBMS

RDF store

Secondary database models

Time Series DBMS

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

Score	2.11
Rank	#118	Overall
	#11	Search engines

Score	0.74
Rank	#222	Overall
	#9	RDF stores

Website

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

www.coveo.com

geospock.com

rdf4j.org

Technical documentation

docs.coveo.com

rdf4j.org/documentation

Developer

Atos Convergence Creators

Coveo

GeoSpock

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2016

2012

2004

Current release

1703

2.0, September 2019

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Java, Javascript

Java

Server operating systems

Linux

hosted

Linux
OS X
Unix
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

RDF Schemas

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

temporal, categorical

yes

SQL

Support of SQL

ANSI SQL for query only (using Presto)

APIs and other access methods

LDAP

RESTful HTTP API

JDBC

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

All languages with LDAP bindings

C#
Java
JavaScript
Python

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

yes

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

yes

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

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

Access rights for users can be defined per table

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