DBMS > Netezza vs. SiriDB vs. Ultipa vs. Vertica

System Properties Comparison Netezza vs. SiriDB vs. Ultipa vs. Vertica

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Editorial information provided by DB-Engines

Name

Description

Data warehouse and analytics appliance part of IBM PureSystems

High performance Graph DBMS supporting HTAP high availability cluster deployment

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

Column oriented

Secondary database models

Spatial DBMS
Time Series DBMS

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

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Score	0.00
Rank	#385	Overall
	#40	Time Series DBMS

Score	0.11
Rank	#338	Overall
	#32	Graph DBMS

Score	9.62
Rank	#42	Overall
	#26	Relational DBMS

Website

www.ibm.com/products/netezza

siridb.com

www.ultipa.com

www.vertica.com

Technical documentation

docs.siridb.com

www.ultipa.com/document

vertica.com/documentation

Developer

IBM

Cesbit

Ultipa

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2000

2017

2019

2005

Current release

12.0.3, January 2023

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

Linux

included in appliance

Linux

Data scheme

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

Typing

predefined data types such as float or date

yes

Numeric data

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

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

JDBC
ODBC
OLE DB

HTTP API

RESTful HTTP API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, hierarchical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

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

User concepts

Access control

Users with fine-grained authorization concept

simple rights management via user accounts

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources

Recent citations in the news

Unify and share data across Netezza and watsonx.data for new generative AI applications
21 June 2024, IBM

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime
21 August 2019, AWS Blog

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

Copy data from Netezza to Azure with Azure Data Factory
9 September 2019, azure.microsoft.com

IBM Completes Acquisition of Netezza
11 November 2010, PR Newswire

provided by Google News

Ultipa, Inc. Announces Key Updates to Its Global Partnership Program
21 August 2024, EIN News

provided by Google News

Vertica on Kubernetes
20 June 2024, blogs.opentext.com

OpenText Analytics Database: The ELT Advantage
9 August 2024, blogs.opentext.com

MapR Hadoop Upgrade Spins YARN, Supports HP Vertica Analytics Platform
31 May 2024, Data Center Knowledge

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

What’s New in OpenText Vertica
10 January 2024, blogs.opentext.com

provided by Google News

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