DBMS > Atos Standard Common Repository vs. Citus vs. Couchbase vs. Snowflake vs. STSdb

System Properties Comparison Atos Standard Common Repository vs. Citus vs. Couchbase vs. Snowflake vs. STSdb

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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

Cloud-based data warehousing service for structured and semi-structured data

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Key-value store

Secondary database models

Document store

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

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

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

www.citusdata.com

www.couchbase.com

www.snowflake.com

github.com/STSSoft/STSdb4

Technical documentation

docs.citusdata.com

docs.couchbase.com

docs.snowflake.net/manuals/index.html

Developer

Atos Convergence Creators

Couchbase, Inc.

Snowflake Computing Inc.

STS Soft SC

Initial release

2016

2010

2011

2014

2011

Current release

1703

8.1, December 2018

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

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

Open Source

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

commercial

Open Source

GPLv2, commercial license available

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, C++, Go and Erlang

Server operating systems

Linux

Linux
OS X
Windows

hosted

Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

optional

yes

primitive types and user defined types (classes)

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

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

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

yes

APIs and other access methods

LDAP

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

CLI Client
JDBC
ODBC

.NET Client API

Supported programming languages

All languages with LDAP bindings

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

C#
Java

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

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

user defined functions

Triggers

yes

via the TAP protocol

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Automatic Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication

including cross data center replication
Source-replica replication

yes

none

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
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 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

fine grained access rights according to SQL-standard

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

Users with fine-grained authorization concept, user roles and pluggable authentication

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