DBMS > Netezza vs. Newts vs. Oracle NoSQL vs. SAP IQ

System Properties Comparison Netezza vs. Newts vs. Oracle NoSQL vs. SAP IQ

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Editorial information provided by DB-Engines

Name

Description

Data warehouse and analytics appliance part of IBM PureSystems

Time Series DBMS based on Cassandra

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Columnar RDBMS optimized for Big Data analytics

Primary database model

Relational DBMS

Time Series DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

column-oriented

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

Score	10.18
Rank	#46	Overall
	#29	Relational DBMS

Score	0.00
Rank	#396	Overall
	#42	Time Series DBMS

Score	2.96
Rank	#103	Overall
	#18	Document stores
	#17	Key-value stores
	#52	Relational DBMS

Score	3.27
Rank	#96	Overall
	#50	Relational DBMS

Website

www.ibm.com/products/netezza

opennms.github.io/newts

www.oracle.com/database/nosql/technologies/nosql

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

Technical documentation

github.com/OpenNMS/newts/wiki

docs.oracle.com/en/database/other-databases/nosql-database/index.html

help.sap.com/docs/SAP_IQ

Developer

IBM

OpenNMS Group

Oracle

SAP, formerly Sybase

Initial release

2000

2014

2011

1994

Current release

23.3, December 2023

16.1 SPS04, April 2019

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

commercial

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

Java

Server operating systems

Linux

included in appliance

Linux
OS X
Windows

Linux
Solaris SPARC/x86

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
ODBC
OLE DB

HTTP REST
Java API

RESTful HTTP API

ADO.NET
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C
C++
Fortran
Java
Lua
Perl
Python
R

Java

C
C#
Go
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

SAP/Sybase Replication Server

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate 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

configurable

ACID within a storage node (=shard)

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

off heap cache

User concepts

Access control

Users with fine-grained authorization concept

Access rights for users and roles

fine grained access rights according to SQL-standard

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More resources

Recent citations in the news

IBM announces availability of the high-performance, cloud-native Netezza Performance Server as a Service on AWS
11 July 2023, IBM

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Migrating your Netezza data warehouse to Amazon Redshift | Amazon Web Services
27 May 2020, AWS Blog

U.S. Navy Chooses Yellowbrick, Sunsets IBM Netezza
22 March 2023, Business Wire

IBM Brings Back a Netezza, Attacks Yellowbrick
29 June 2020, Datanami

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3 April 2014, Data Center Knowledge

Oracle Defends Relational DBs Against NoSQL Competitors
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7 April 2021, SAP News

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2 July 2021, Datamation

Independent Research Firm Names SAP a Leader in Data Management for Analytics
17 February 2020, SAP News

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6 March 2014, EnterpriseAI

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22 April 2014, PR Newswire

provided by Google News

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