Average Ratings 0 Ratings
Average Ratings 0 Ratings
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
Zypper serves as a command-line package management tool, allowing users to install, update, and remove software packages efficiently. Moreover, it provides functionality for repository management, behaving consistently like other command-line utilities. With its array of subcommands, arguments, and options, Zypper allows users to carry out specific tasks efficiently. Its advantages over graphical package managers are noteworthy, as being a command-line tool enables Zypper to operate more rapidly and consume fewer system resources. Additionally, its actions can be easily scripted, which enhances automation capabilities. Zypper is particularly advantageous for servers and remote machines that lack graphical desktop environments, making it a versatile choice for system administrators. To use Zypper, simply type its name followed by the desired command, and you can also include one or more global options directly before the command. Certain commands may require additional arguments for completion. However, it is important to note that executing subcommands within the Zypper shell and utilizing global Zypper options simultaneously is not supported. This limitation should be taken into account when planning to use Zypper for package management tasks.
API Access
Has API
No
API Access
Has API
No
Integrations
3forge
Yes
Advanced Query Tool (AQT)
Yes
Amazon S3
Yes
Coginiti
Yes
Datametica
Yes
DbVisualizer
Yes
Digna
Yes
IBM Cloud
Yes
IBM Cloud Pak for Data
Yes
IBM Cognos Analytics
Yes
Integrations
3forge
No
Advanced Query Tool (AQT)
No
Amazon S3
No
Coginiti
No
Datametica
No
DbVisualizer
No
Digna
No
IBM Cloud
No
IBM Cloud Pak for Data
No
IBM Cognos Analytics
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
Free
Free Trial
No
Free Version
Yes
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
No
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
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
Yes
Webinars
No
Live Training (Online)
No
In Person
Yes
Vendor Details
Company Name
IBM
Founded
1911
Country
United States
Website
www.ibm.com/products/netezza
Vendor Details
Company Name
SUSE
Country
United States
Website
documentation.suse.com/smart/linux/html/concept-zypper/index.html
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