DBMS > IBM Db2 vs. Informix vs. Memcached vs. Microsoft Azure Cosmos DB vs. Netezza

System Properties Comparison IBM Db2 vs. Informix vs. Memcached vs. Microsoft Azure Cosmos DB vs. Netezza

Editorial information provided by DB-Engines

Name

Description

Common in IBM host environments, 2 different versions for host and Windows/Linux

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

In-memory key-value store, originally intended for caching

Globally distributed, horizontally scalable, multi-model database service

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Relational DBMS

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

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

Spatial DBMS

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

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

Score	17.87
Rank	#35	Overall
	#22	Relational DBMS

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

www.ibm.com/products/db2

www.ibm.com/products/informix

www.memcached.org

azure.microsoft.com/services/cosmos-db

www.ibm.com/products/netezza

Technical documentation

www.ibm.com/docs/en/db2

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

github.com/memcached/memcached/wiki

learn.microsoft.com/azure/cosmos-db

Developer

IBM

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.

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Microsoft

IBM

Initial release

1983

host version

1984

2003

2014

2000

Current release

12.1, October 2016

14.10.FC5, November 2020

1.6.27, May 2024

License

Commercial or Open Source

commercial

free version is available

commercial

free developer edition available

Open Source

BSD license

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

C and C++

C, C++ and Java

Server operating systems

AIX
HP-UX
Linux
Solaris
Windows
z/OS

AIX
HP-UX
Linux
macOS
Solaris
Windows

FreeBSD
Linux
OS X
Unix
Windows

hosted

Linux

included in appliance

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

JSON types

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JDBC
JSON API

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

Proprietary protocol

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JDBC
ODBC
OLE DB

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

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

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

JavaScript

yes

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

Sharding

none

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

Multi-source replication
Source-replica replication

none

Repcached, a Memcached patch, provides this functionallity

yes

Implicit feature of the cloud service

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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

User concepts

Access control

fine grained access rights according to SQL-standard

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

yes

using SASL (Simple Authentication and Security Layer) protocol

Access rights can be defined down to the item level

Users with fine-grained authorization concept

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