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Average Ratings 0 Ratings

Total
ease
features
design
support

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Write a Review

Description

Fully compatible with Netezza, this solution offers a streamlined command-line upgrade option. It can be deployed on-premises, in the cloud, or through a hybrid model. The IBM® Netezza® Performance Server for IBM Cloud Pak® for Data serves as a sophisticated platform for data warehousing and analytics, catering to both on-premises and cloud environments. With significant improvements in in-database analytics functions, this next-generation Netezza empowers users to engage in data science and machine learning with datasets that can reach petabyte levels. It includes features for detecting failures and ensuring rapid recovery, making it robust for enterprise use. Users can upgrade existing systems using a single command-line interface. The platform allows for querying multiple systems as a cohesive unit. You can select the nearest data center or availability zone, specify the desired compute units and storage capacity, and initiate the setup seamlessly. Furthermore, the IBM® Netezza® Performance Server is accessible on IBM Cloud®, Amazon Web Services (AWS), and Microsoft Azure, and it can also be implemented on a private cloud, all powered by the capabilities of IBM Cloud Pak for Data System. This flexibility enables organizations to tailor the deployment to their specific needs and infrastructure.

Description

Qlik Compose for Data Warehouses offers a contemporary solution that streamlines and enhances the process of establishing and managing data warehouses. This tool not only automates the design of the warehouse but also generates ETL code and implements updates swiftly, all while adhering to established best practices and reliable design frameworks. By utilizing Qlik Compose for Data Warehouses, organizations can significantly cut down on the time, expense, and risk associated with BI initiatives, regardless of whether they are deployed on-premises or in the cloud. On the other hand, Qlik Compose for Data Lakes simplifies the creation of analytics-ready datasets by automating data pipeline processes. By handling data ingestion, schema setup, and ongoing updates, companies can achieve a quicker return on investment from their data lake resources, further enhancing their data strategy. Ultimately, these tools empower organizations to maximize their data potential efficiently.

API Access

Has API No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

Amazon S3 Yes 
BLUE Software No 
Captain Compliance Yes 
DbVisualizer Yes 
IBM Cloud Yes 
IBM Cloud Pak for Data Yes 
IBM Cognos Analytics Yes 
IBM watsonx.data Yes 
Immuta Yes 
Impetus Yes 
Lyftrondata Yes 
Microsoft Azure Yes 
Rayven No 
RazorSQL Yes 
SOLIXCloud CDP Yes 
Semarchy xDI Yes 
StreamFlux Yes 
Style Intelligence Yes 
Tenant No 

Integrations

Amazon S3 No 
BLUE Software Yes 
Captain Compliance No 
DbVisualizer No 
IBM Cloud No 
IBM Cloud Pak for Data No 
IBM Cognos Analytics No 
IBM watsonx.data No 
Immuta No 
Impetus No 
Lyftrondata No 
Microsoft Azure No 
Rayven Yes 
RazorSQL No 
SOLIXCloud CDP No 
Semarchy xDI No 
StreamFlux No 
Style Intelligence No 
Tenant Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows Yes 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours No 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

Types of Training

Training Docs No 
Webinars No 
Live Training (Online) No 
In Person No 

Vendor Details

Company Name

IBM

Founded

1911

Country

United States

Website

www.ibm.com/products/netezza

Vendor Details

Company Name

Qlik

Founded

1993

Country

United States

Website

www.qlik.com/us/products/qlik-compose-data-warehouses

Product Features

Data Warehouse

Ad hoc Query No 
Analytics No 
Data Integration No 
Data Migration No 
Data Quality Control No 
ETL - Extract / Transfer / Load No 
In-Memory Processing No 
Match & Merge No 

Product Features

Data Warehouse

Ad hoc Query No 
Analytics Yes 
Data Integration Yes 
Data Migration No 
Data Quality Control No 
ETL - Extract / Transfer / Load No 
In-Memory Processing No 
Match & Merge No 

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