DBMS > Atos Standard Common Repository vs. OrigoDB vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. OrigoDB vs. Spark SQL

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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

A fully ACID in-memory object graph database

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store
Key-value store

Document store
Object oriented DBMS

Relational DBMS

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

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

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

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

origodb.com

spark.apache.org/sql

Technical documentation

origodb.com/docs

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Atos Convergence Creators

Robert Friberg et al

Apache Software Foundation

Initial release

2016

2009

under the name LiveDB

2014

Current release

1703

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Scala

Server operating systems

Linux

Linux
Windows

Linux
OS X
Windows

Data scheme

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

LDAP

.NET Client API
HTTP API
LINQ

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

.Net

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning

client side managed; servers are not synchronized

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

none

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

Foreign keys

Referential integrity

depending on model

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

Write ahead log

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

Role based authorization

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