DBMS > Atos Standard Common Repository vs. Couchbase vs. OpenQM vs. TerminusDB vs. YDB

System Properties Comparison Atos Standard Common Repository vs. Couchbase vs. OpenQM vs. TerminusDB vs. YDB

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 distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

QpenQM is a high-performance, self-tuning, multi-value DBMS

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

A distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API

Primary database model

Document store
Key-value store

Document store

Multivalue DBMS

Graph DBMS

Document store
Relational DBMS

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Document store
RDF store

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	0.27
Rank	#298	Overall
	#10	Multivalue DBMS

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Score	0.35
Rank	#278	Overall
	#43	Document stores
	#127	Relational DBMS

Website

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

www.couchbase.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

terminusdb.com

github.com/ydb-platform/ydb
ydb.tech

Technical documentation

docs.couchbase.com

terminusdb.github.io/terminusdb/#

ydb.tech/en/docs

Developer

Atos Convergence Creators

Couchbase, Inc.

Rocket Software, originally Martin Phillips

DataChemist Ltd.

Yandex

Initial release

2016

2011

1993

2018

2019

Current release

1703

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

3.4-12

11.0.0, January 2023

License

Commercial or Open Source

commercial

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

GPLv2, extended commercial license available

Open Source

GPL V3

Open Source

Apache 2.0; commercial license available

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, C++, Go and Erlang

Prolog, Rust

Server operating systems

Linux

Linux
OS X
Windows

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

with some exceptions

yes

Flexible Schema (defined schema, partial schema, schema free)

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

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

SQL-like query language (WOQL)

SQL-like query language (YQL)

APIs and other access methods

LDAP

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

RESTful HTTP API (DynamoDB compatible)

Supported programming languages

All languages with LDAP bindings

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
Basic
C
Java
Objective C
PHP
Python

JavaScript
Python

Go
Java
JavaScript (Node.js)
PHP
Python

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Automatic Sharding

yes

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

yes

Journaling Streams

Active-passive shard 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

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

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

in-memory journaling

yes

In-memory capabilities

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

yes

Ephemeral buckets

User concepts

Access control

LDAP bind authentication

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Access rights can be defined down to the item level

Role-based access control

Access rights defined for Yandex Cloud users

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