DBMS > Informix vs. Microsoft Azure Table Storage vs. MySQL vs. openGauss

System Properties Comparison Informix vs. Microsoft Azure Table Storage vs. MySQL vs. openGauss

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Editorial information provided by DB-Engines

Name

Description

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

A Wide Column Store for rapid development using massive semi-structured datasets

Widely used open source RDBMS

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

Primary database model

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Wide column store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

Document store
Spatial DBMS

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

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Website

www.ibm.com/products/informix

azure.microsoft.com/en-us/services/storage/tables

www.mysql.com

gitee.com/opengauss
opengauss.org

Technical documentation

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

dev.mysql.com/doc

docs.opengauss.org/en
gitee.com/opengauss/docs

Developer

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Huawei and openGauss community

Initial release

1984

2012

1995

2019

Current release

14.10.FC5, November 2020

8.4.0, April 2024

3.0, March 2022

License

Commercial or Open Source

commercial

free developer edition available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++ and Java

C and C++

C, C++, Java

Server operating systems

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

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

with proprietary extensions

ANSI SQL 2011

APIs and other access methods

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
ODBC

Supported programming languages

.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

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

C
C++
Java

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning (by range, list and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

optimistic locking

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

User concepts

Access control

Users with fine-grained authentication, authorization, and auditing controls

Access rights based on private key authentication or shared access signatures

Users with fine-grained authorization concept

no user groups or roles

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

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