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What is IBM Netezza Performance Server?

This solution, which is fully compatible with Netezza, provides a smooth command-line upgrade option that enhances user experience. It can be utilized in various configurations, including on-premises, cloud-based, or hybrid setups. The IBM® Netezza® Performance Server for IBM Cloud Pak® for Data serves as an advanced platform designed for data warehousing and analytics, effectively addressing the needs of both cloud and on-premises environments. With enhanced in-database analytics capabilities, this next-gen Netezza empowers users to perform data science and machine learning operations on datasets that can scale up to petabytes. Its robust features include failure detection and rapid recovery systems, making it ideal for enterprise applications. Upgrading existing systems is simplified by using a unified command-line interface. Moreover, the platform allows users to query multiple systems as if they were a single entity, enhancing operational efficiency. Users can choose the closest data center or availability zone, define their preferred compute units and storage requirements, and initiate setup with ease. Additionally, the IBM® Netezza® Performance Server is available on IBM Cloud®, Amazon Web Services (AWS), and Microsoft Azure, and it can also be deployed on a private cloud, utilizing the full potential of IBM Cloud Pak for Data System. This adaptability allows organizations to customize their deployment according to their unique requirements and technological infrastructure, ensuring they can optimize their data strategies effectively. Furthermore, with its user-friendly features, businesses can easily scale their operations as needed.

What is Dimodelo?

Focus on crafting meaningful and influential reports and analytics instead of getting overwhelmed by the intricacies of data warehouse coding. It's essential to prevent your data warehouse from devolving into a disorganized collection of numerous challenging pipelines, notebooks, stored procedures, tables, and views. Dimodelo DW Studio significantly reduces the effort required for the design, construction, deployment, and management of a data warehouse. It supports the creation and implementation of a data warehouse tailored for Azure Synapse Analytics. By establishing a best practice architecture that integrates Azure Data Lake, Polybase, and Azure Synapse Analytics, Dimodelo Data Warehouse Studio guarantees the provision of a high-performing and modern cloud data warehouse. Additionally, the use of parallel bulk loads and in-memory tables further enhances the efficiency of Dimodelo Data Warehouse Studio, allowing teams to prioritize extracting valuable insights over handling maintenance tasks. This shift not only streamlines operations but also empowers organizations to make data-driven decisions with greater agility.

Media

Media

Integrations Supported

Microsoft Azure
Advanced Query Tool (AQT)
Amazon S3
Arcion
Coginiti
DBHawk
Datametica
IBM Cloud
IBM Cloud Pak for Data
IBM Cognos Analytics
IBM watsonx.data
Immuta
Microsoft 365
Microsoft Power BI
SMART Business Suite
SOLIXCloud
SQL Server
Semarchy xDI
StreamFlux
Tableau Catalog

Integrations Supported

Microsoft Azure
Advanced Query Tool (AQT)
Amazon S3
Arcion
Coginiti
DBHawk
Datametica
IBM Cloud
IBM Cloud Pak for Data
IBM Cognos Analytics
IBM watsonx.data
Immuta
Microsoft 365
Microsoft Power BI
SMART Business Suite
SOLIXCloud
SQL Server
Semarchy xDI
StreamFlux
Tableau Catalog

API Availability

Has API

API Availability

Has API

Pricing Information

Pricing not provided.
Free Trial Offered?
Free Version

Pricing Information

$899 per month
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/products/netezza

Company Facts

Organization Name

Dimodelo

Company Location

Australia

Company Website

www.dimodelo.com

Categories and Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

Categories and Features

Data Warehouse

Ad hoc Query
Analytics
Data Integration
Data Migration
Data Quality Control
ETL - Extract / Transfer / Load
In-Memory Processing
Match & Merge

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