DBMS > Atos Standard Common Repository vs. BigObject vs. Blueflood vs. eXtremeDB vs. RDFox

System Properties Comparison Atos Standard Common Repository vs. BigObject vs. Blueflood vs. eXtremeDB vs. RDFox

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

Scalable TimeSeries DBMS based on Cassandra

Natively in-memory DBMS with options for persistency, high-availability and clustering

High performance knowledge graph and semantic reasoning engine

Primary database model

Document store
Key-value store

Relational DBMS

a hierachical model (tree) can be imposed

Time Series DBMS

Relational DBMS
Time Series DBMS

Graph DBMS
RDF store

Secondary database models

Relational DBMS

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

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	0.06
Rank	#352	Overall
	#36	Time Series DBMS

Score	0.79
Rank	#212	Overall
	#100	Relational DBMS
	#18	Time Series DBMS

Score	0.22
Rank	#305	Overall
	#25	Graph DBMS
	#15	RDF stores

Website

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

bigobject.io

blueflood.io

www.mcobject.com

www.oxfordsemantic.tech

Technical documentation

docs.bigobject.io

github.com/rax-maas/blueflood/wiki

www.mcobject.com/docs/extremedb.htm

docs.oxfordsemantic.tech

Developer

Atos Convergence Creators

BigObject, Inc.

Rackspace

McObject

Oxford Semantic Technologies

Initial release

2016

2015

2013

2001

2017

Current release

1703

8.2, 2021

6.0, Septermber 2022

License

Commercial or Open Source

commercial

free community edition available

Open Source

Apache 2.0

commercial

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 and C++

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
OS X

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux
macOS
Windows

Data scheme

Schema and schema-less with LDAP views

yes

predefined scheme

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

support of XML interfaces available

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

with the option: eXtremeSQL

APIs and other access methods

LDAP

fluentd
ODBC
RESTful HTTP API

HTTP REST

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

RESTful HTTP API
SPARQL 1.1

Supported programming languages

All languages with LDAP bindings

.Net
C
C#
C++
Java
Lua
Python
Scala

C
Java

Server-side scripts

Stored procedures

Lua

yes

Triggers

yes

by defining events

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

based on Cassandra

horizontal partitioning / sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

based on Cassandra

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

replication via a shared file system

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

none

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

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

Optimistic (MVCC) and pessimistic (locking) strategies available

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

Roles, resources, and access types

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