DBMS > Atos Standard Common Repository vs. BigObject vs. DataFS vs. Elasticsearch

System Properties Comparison Atos Standard Common Repository vs. BigObject vs. DataFS vs. Elasticsearch

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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

Analytic DBMS for real-time computations and queries

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Primary database model

Document store
Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Object oriented DBMS

Search engine

Secondary database models

Graph DBMS

Document store
Spatial DBMS
Vector DBMS

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

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	128.79
Rank	#8	Overall
	#1	Search engines

Website

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

bigobject.io

newdatabase.com

www.elastic.co/elasticsearch

Technical documentation

docs.bigobject.io

dev.mobiland.com/Overview.xsp

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

Developer

Atos Convergence Creators

BigObject, Inc.

Mobiland AG

Elastic

Initial release

2016

2015

2018

2010

Current release

1703

1.1.263, October 2022

8.6, January 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

Elastic License

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

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Windows

All OS with a Java VM

Data scheme

Schema and schema-less with LDAP views

yes

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

All search fields are automatically indexed

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

LDAP

fluentd
ODBC
RESTful HTTP API

.NET Client API
Proprietary client DLL
WinRT client

Java API
RESTful HTTP/JSON API

Supported programming languages

All languages with LDAP bindings

.Net
C
C#
C++
VB.Net

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

Lua

yes

Triggers

yes

no, except callback-events from server when changes happened

yes

by using the 'percolation' feature

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Proprietary Sharding system

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

none

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

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

Read/write lock on objects (tables, trees)

yes

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

Memcached and Redis integration

User concepts

Access control

LDAP bind authentication

Windows-Profile

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