DBMS > Kinetica vs. Microsoft SQL Server vs. Netezza vs. OpenQM

System Properties Comparison Kinetica vs. Microsoft SQL Server vs. Netezza vs. OpenQM

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Editorial information provided by DB-Engines

Name

Description

Fully vectorized database across both GPUs and CPUs

Microsofts flagship relational DBMS

Data warehouse and analytics appliance part of IBM PureSystems

QpenQM is a high-performance, self-tuning, multi-value DBMS

Primary database model

Relational DBMS

Multivalue DBMS

Secondary database models

Spatial DBMS
Time Series DBMS

Document store
Graph DBMS
Spatial DBMS

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

Score	0.69
Rank	#234	Overall
	#107	Relational DBMS

Score	829.80
Rank	#3	Overall
	#3	Relational DBMS

Score	10.18
Rank	#46	Overall
	#29	Relational DBMS

Score	0.33
Rank	#286	Overall
	#10	Multivalue DBMS

Website

www.kinetica.com

www.microsoft.com/en-us/sql-server

www.ibm.com/products/netezza

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

Technical documentation

docs.kinetica.com

learn.microsoft.com/en-US/sql/sql-server

Developer

Kinetica

Microsoft

IBM

Rocket Software, originally Martin Phillips

Initial release

2012

1989

2000

1993

Current release

7.1, August 2021

SQL Server 2022, November 2022

3.4-12

License

Commercial or Open Source

commercial

restricted free version is available

commercial

Open Source

GPLv2, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C, C++

C++

Server operating systems

Linux

Linux
Windows

Linux

included in appliance

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Data scheme

yes

with some exceptions

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

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

JDBC
ODBC
OLE DB

Supported programming languages

C++
Java
JavaScript (Node.js)
Python

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net
Basic
C
Java
Objective C
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, but depending on the SQL-Server Edition

Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

GPU vRAM or System RAM

yes

User concepts

Access control

Access rights for users and roles on table level

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

Access rights can be defined down to the item level

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