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What is Rocket Data Virtualization?
Traditional methods for integrating mainframe data, like ETL, data warehouses, and connector development, are becoming increasingly insufficient in terms of speed, accuracy, and efficiency in the current business environment. With the ever-growing volume of data generated and stored on mainframes, these timeworn approaches are increasingly outpaced. Data virtualization presents itself as a modern solution to this widening gap, streamlining the access of mainframe data for both developers and applications. This innovative method enables organizations to identify and map their data just once, allowing for easy virtualization and reuse across multiple platforms. Consequently, this capability ensures that data remains in alignment with overarching business objectives and goals. By implementing data virtualization on z/OS, organizations can effectively navigate the complexities associated with mainframe resources. Furthermore, data virtualization promotes the integration of information from various disparate sources into a unified logical repository, which significantly enhances the connection between mainframe data and distributed applications. In addition, this technique allows for the enrichment of mainframe data through the incorporation of insights derived from location, social media, and other external datasets, leading to a more holistic understanding of business dynamics. As organizations seek to remain competitive, embracing such advanced methodologies can foster agility and innovation in decision-making processes.
What is IBM DataStage?
Accelerate the development of AI innovations with the cloud-native data integration solutions provided by IBM Cloud Pak for Data. With AI-enhanced data integration functionalities available from any location, the impact of your AI and analytics initiatives is closely tied to the caliber of the underlying data. Leveraging a contemporary container-based framework, IBM® DataStage® within IBM Cloud Pak® for Data guarantees the provision of high-quality data. This offering combines exceptional data integration with DataOps, governance, and analytics into a cohesive data and AI ecosystem. By streamlining administrative processes, it contributes to a reduction in total cost of ownership (TCO). The platform's AI-driven design accelerators, in conjunction with readily available integrations for DataOps and data science services, significantly expedite the pace of AI development. Moreover, its capabilities for parallel processing and multicloud integration facilitate the delivery of consistent data across extensive hybrid or multicloud environments. Additionally, the IBM Cloud Pak for Data platform allows for the effective management of the complete data and analytics lifecycle, incorporating a range of services such as data science, event messaging, data virtualization, and data warehousing, all supported by a parallel engine and automated load balancing. This all-encompassing strategy equips your organization to remain at the forefront of the swiftly changing data and AI landscape, ensuring that you can adapt and thrive in a competitive market.
Integrations Supported
ActiveBatch Workload Automation
BMC AMI Ops Automation for Capping
FairCom DB
FairCom EDGE
IBM Cloud
IBM Cloud Pak for Applications
IBM Watson Studio
IRI FieldShield
MettleCI
Origina
Integrations Supported
ActiveBatch Workload Automation
BMC AMI Ops Automation for Capping
FairCom DB
FairCom EDGE
IBM Cloud
IBM Cloud Pak for Applications
IBM Watson Studio
IRI FieldShield
MettleCI
Origina
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
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
Rocket
Date Founded
1990
Company Location
United States
Company Website
www.rocketsoftware.com/product-categories/data-virtualization
Company Facts
Organization Name
IBM
Date Founded
1911
Company Location
United States
Company Website
www.ibm.com/products/infosphere-datastage
Categories and Features
Categories and Features
Big Data
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Lineage
Database Change Impact Analysis
Filter Lineage Links
Implicit Connection Discovery
Lineage Object Filtering
Object Lineage Tracing
Point-in-Time Visibility
User/Client/Target Connection Visibility
Visual & Text Lineage View
ETL
Data Analysis
Data Filtering
Data Quality Control
Job Scheduling
Match & Merge
Metadata Management
Non-Relational Transformations
Version Control