DBMS > Atos Standard Common Repository vs. DataFS vs. Infobright vs. Riak TS vs. Rockset

System Properties Comparison Atos Standard Common Repository vs. DataFS vs. Infobright vs. Riak TS vs. Rockset

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

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.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Document store
Key-value store

Secondary database models

Graph DBMS

Relational DBMS
Search engine

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

Score	0.06
Rank	#354	Overall
	#15	Object oriented DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

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

newdatabase.com

ignitetech.com/softwarelibrary/infobrightdb

rockset.com

Technical documentation

dev.mobiland.com/Overview.xsp

www.tiot.jp/riak-docs/riak/ts/latest

docs.rockset.com

Developer

Atos Convergence Creators

Mobiland AG

Ignite Technologies Inc.; formerly InfoBright Inc.

Open Source, formerly Basho Technologies

Rockset

Initial release

2016

2018

2005

2015

2019

Current release

1703

1.1.263, October 2022

3.0.0, September 2022

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

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

Erlang

C++

Server operating systems

Linux

Windows

Linux
Windows

Linux
OS X

hosted

Data scheme

Schema and schema-less with LDAP views

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

yes

schema-free

Typing

predefined data types such as float or date

optional

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

Knowledge Grid Technology used instead

restricted

all fields are automatically indexed

SQL

Support of SQL

yes

yes, limited

Read-only SQL queries, including JOINs

APIs and other access methods

LDAP

.NET Client API
Proprietary client DLL
WinRT client

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

HTTP REST

Supported programming languages

All languages with LDAP bindings

.Net
C
C#
C++
VB.Net

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Erlang

Triggers

yes

no, except callback-events from server when changes happened

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Proprietary Sharding system

none

Sharding

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

selectable replication factor

yes

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

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

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

Windows-Profile

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Access rights for users and organizations can be defined via Rockset console

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