DBMS > Atos Standard Common Repository vs. EsgynDB vs. Google BigQuery vs. Infobright vs. OrigoDB

System Properties Comparison Atos Standard Common Repository vs. EsgynDB vs. Google BigQuery vs. Infobright vs. OrigoDB

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Large scale data warehouse service with append-only tables

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

A fully ACID in-memory object graph database

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Object oriented DBMS

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

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

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

www.esgyn.cn

cloud.google.com/bigquery

ignitetech.com/softwarelibrary/infobrightdb

origodb.com

Technical documentation

cloud.google.com/bigquery/docs

origodb.com/docs

Developer

Atos Convergence Creators

Esgyn

Google

Ignite Technologies Inc.; formerly InfoBright Inc.

Robert Friberg et al

Initial release

2016

2015

2010

2005

2009

under the name LiveDB

Current release

1703

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

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

C++, Java

Server operating systems

Linux

hosted

Linux
Windows

Data scheme

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

yes

APIs and other access methods

LDAP

ADO.NET
JDBC
ODBC

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

.NET Client API
HTTP API
LINQ

Supported programming languages

All languages with LDAP bindings

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

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

.Net

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions

in JavaScript

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

Source-replica replication

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

Foreign keys

Referential integrity

yes

depending on model

Transaction concepts

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

Atomic execution of specific operations

ACID

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

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

fine grained access rights according to SQL-standard

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

Role based authorization

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