DBMS > Atos Standard Common Repository vs. BigObject vs. EJDB vs. Hypertable vs. Newts

System Properties Comparison Atos Standard Common Repository vs. BigObject vs. EJDB vs. Hypertable vs. Newts

Editorial information provided by DB-Engines

Name

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

Hypertable has stopped its further development with March 2016 and is 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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

An open source BigTable implementation based on distributed file systems such as Hadoop

Time Series DBMS based on Cassandra

Primary database model

Document store
Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Document store

Wide column store

Time Series DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Website

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

bigobject.io

github.com/Softmotions/ejdb

opennms.github.io/newts

Technical documentation

docs.bigobject.io

github.com/Softmotions/ejdb/blob/master/README.md

github.com/OpenNMS/newts/wiki

Developer

Atos Convergence Creators

BigObject, Inc.

Softmotions

Hypertable Inc.

OpenNMS Group

Initial release

2016

2015

2012

2009

2014

Current release

1703

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

free community edition available

Open Source

GPLv2

Open Source

GNU version 3. Commercial license available

Open Source

Apache 2.0

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++

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)

server-less

Linux
OS X
Windows

an inofficial Windows port is available

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

Typing

predefined data types such as float or date

optional

yes

string, integer, double, bool, date, object_id

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

restricted

only exact value or prefix value scans

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

LDAP

fluentd
ODBC
RESTful HTTP API

in-process shared library

C++ API
Thrift

HTTP REST
Java API

Supported programming languages

All languages with LDAP bindings

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

Java

Server-side scripts

Stored procedures

Lua

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor on file system level

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

Atomic execution of specific operations

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Read/Write Locking

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

User concepts

Access control

LDAP bind authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Infographic: What makes a Mobile Operator's setup future proof?
10 February 2024, Atos

provided by Google News

SQL and TimescaleDB. This article takes a closer look into… | by Alibaba Cloud
31 July 2019, DataDrivenInvestor

TimescaleDB goes distributed; implements ‘Chunking’ over ‘Sharding’ for scaling-out
22 August 2019, Packt Hub

Decorate your Windows XP with Hyperdesk
30 July 2008, CNET

The Collective: Customize Your Computer & Your Phone With Star Trek
18 March 2009, TrekMovie

NoSQL Market: A well-defined technological growth map with an impact-analysis
19 June 2020, Inter Press Service

provided by Google News

Share this page