DBMS > Atos Standard Common Repository vs. Couchbase vs. Cubrid vs. etcd vs. Microsoft Azure Synapse Analytics

System Properties Comparison Atos Standard Common Repository vs. Couchbase vs. Cubrid vs. etcd vs. Microsoft Azure Synapse Analytics

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

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

A distributed reliable key-value store

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Primary database model

Document store
Key-value store

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

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

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	1.04
Rank	#187	Overall
	#87	Relational DBMS

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Website

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

www.couchbase.com

cubrid.com (korean)
cubrid.org (english)

etcd.io
github.com/etcd-io/etcd

azure.microsoft.com/services/synapse-analytics

Technical documentation

docs.couchbase.com

cubrid.org/manuals

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.microsoft.com/azure/synapse-analytics

Developer

Atos Convergence Creators

Couchbase, Inc.

CUBRID Corporation, CUBRID Foundation

Microsoft

Initial release

2016

2011

2008

2016

Current release

1703

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

11.0, January 2021

3.4, August 2019

License

Commercial or Open Source

commercial

Open Source

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

Open Source

Apache Version 2.0

Open Source

Apache Version 2.0

commercial

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

C, C++, Java

C++

Server operating systems

Linux

Linux
OS X
Windows

Linux
Windows

FreeBSD
Linux
Windows

experimental

hosted

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

schema-free

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

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

yes

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

ADO.NET
JDBC
ODBC
OLE DB

gRPC
JSON over HTTP

ADO.NET
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C#
Java
PHP

Server-side scripts

Stored procedures

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

Java Stored Procedures

Transact SQL

Triggers

yes

via the TAP protocol

yes

yes, watching key changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Automatic Sharding

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

Source-replica replication

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

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

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

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

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

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.