DBMS > Atos Standard Common Repository vs. Datomic vs. Microsoft Azure AI Search vs. OpenTenBase

System Properties Comparison Atos Standard Common Repository vs. Datomic vs. Microsoft Azure AI Search vs. OpenTenBase

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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

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Search-as-a-service for web and mobile app development

An enterprise-level distributed HTAP open source database based on PostgreSQL

Primary database model

Document store
Key-value store

Relational DBMS

Search engine

Relational DBMS

Secondary database models

Vector DBMS

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

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	5.75
Rank	#58	Overall
	#7	Search engines

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

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

www.datomic.com

azure.microsoft.com/en-us/services/search

github.com/OpenTenBase/OpenTenBase
www.opentenbase.org

Technical documentation

docs.datomic.com

learn.microsoft.com/en-us/azure/search

docs.opentenbase.org
docs.opentenbase.org/en

Developer

Atos Convergence Creators

Cognitect

Microsoft

OpenAtom Foundation, previously Tencent

Initial release

2016

2012

2015

Current release

1703

1.0.7180, July 2024

2.5, January 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

BSD-3

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

Java, Clojure

Server operating systems

Linux

All OS with a Java VM

hosted

Linux

Data scheme

Schema and schema-less with LDAP views

yes

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

LDAP

RESTful HTTP API

Supported programming languages

All languages with LDAP bindings

Clojure
Java

C#
Java
JavaScript
Python

C
Go
Java
PHP
Python

Server-side scripts

Stored procedures

yes

Transaction Functions

Triggers

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

But extensive use of caching in the application peers

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

But extensive use of caching in the application peers

yes

Implicit feature of the cloud service

yes

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

Immediate Consistency

Foreign keys

Referential integrity

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

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

User concepts

Access control

LDAP bind authentication

yes

using Azure authentication

Access rights for users, groups and roles according to SQL-standard

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