DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. CouchDB vs. MariaDB vs. MySQL

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. CouchDB vs. MariaDB vs. MySQL

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Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

MySQL application compatible open source RDBMS, enhanced with high availability, security, interoperability and performance capabilities. MariaDB ColumnStore provides a column-oriented storage engine and MariaDB Xpand supports distributed SQL.

Widely used open source RDBMS

Primary database model

Relational DBMS

Document store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Spatial DBMS

using the Geocouch extension

Document store
Graph DBMS

with OQGraph storage engine
Spatial DBMS

Document store
Spatial DBMS

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	93.21
Rank	#13	Overall
	#9	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

couchdb.apache.org

mariadb.com

Site of MariaDB Corporation
mariadb.org

Site of MariaDB Foundation

www.mysql.com

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

docs.couchdb.org/en/stable

mariadb.com/kb/en/library

dev.mysql.com/doc

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

MariaDB Corporation Ab (MariaDB Enterprise),
MariaDB Foundation (community MariaDB Server)

The lead developer Monty Widenius is the original author of MySQL

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2016

2005

2009

Fork of MySQL, which was first released in 1995

1995

Current release

3.3.3, December 2023

11.3.2, February 2024

8.3.0, January 2024

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

GPL version 2, commercial enterprise subscription available

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Erlang

C and C++

Server operating systems

hosted

Android
BSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
Solaris
Windows

ColumnStore storage engine not available on Windows

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Dynamic columns are supported

yes

Typing

predefined data types such as float or date

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

via views

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

C
Java
Perl
Python
R

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Ada
C
C#
C++
D
Eiffel
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

View functions in JavaScript

yes

PL/SQL compatibility added with version 10.3

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

improved architecture with release 2.0

several options for horizontal partitioning and Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

not for MyISAM storage engine

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

atomic operations within a single document possible

ACID

not for MyISAM storage engine

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

yes

not for in-memory storage engine

yes

In-memory capabilities

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

yes

with MEMORY storage engine

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Web, SaaS and Cloud operational applications that require high availability, scalability...
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Key customers

Deutsche Bank, DBS Bank, Nasdaq, Red Hat, ServiceNow, Verizon and Walgreens Featured...
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Market metrics

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Licensing and pricing models

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