Overview

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IBM Data Virtualization Manager for z/OS provides real time access to data stored in mainframe and universal access to data regardless of location or interface, with low mainframe Total Cost of Ownership (TCO). It also provides increased flexibility for sharing and integrating mainframe with other data sources and applications in real time.

Data Virtualization Manager supports real-time data virtualization solutions for enabling mainframe relational and non-relational data to seamlessly integrate with data analytic, Big Data, mobile, and web solutions. Data Virtualization Manager can be used by any client application program, any load process, or any mainframe program that needs to read/update/delete any data structure resides in Mainframe and LUW (Linux Unix Windows) environments. All underlying data structures are abstracted from the user.

You use Data Virtualization Manager to:

  • Create virtual and integrated views of data to enable you to access mainframe data without having to move, replicate, or transform your source data.
  • Enable access, update, and join functions on your mainframe data with other enterprise data using modern APIs in real-time.
  • Mask your mainframe data implementations from application developers.

    You can safely expose your mainframe assets as APIs that developers can use to incorporate data and transactions into mobile and cloud applications. Additionally, developers can use ANSI SQL functions to retrieve any data in Mainframe and LUW environments.

Data Virtualization Manager server uses the IBM System z Integrated Information Processor (zIIP) for all of its computationally intensive processing. To ensure the highest levels of performance, Data Virtualization Manager server includes several query optimization features, such as parallel input/output and MapReduce. Data Virtualization Manager server employs multiple, parallel threads to handle input request for data and output delivery of information to the client (data consumer). Once data is transformed from non-relational to a relational format, the powerful data virtualization engine continually streams and buffers data to the client.

Data Virtualization Manager 1.2 features

  • Extraction of DBDs and PSBs using IMS Catalog Node.

    For more information, see Extracting DBDs and PSBs using IMS Catalog Node.

  • Multiple Schema Support.
    For more information, see
  • Access to DVM data sources on IBM Cloud Pak for Data.
  • Create RESTful services to access all Db2 objects such as Db2 tables, views, stored procedures, and user-defined table functions (Studs) with the DVM studio.

    For more information, see Creating RESTful services.

  • Extend IBM z/OS Connect EE (zCEE) RESTful services to Db2 objects.
  • Software configuration management capabilities for virtual views:
    • Allows modification of a virtual directory's map and microflow data set names during batch migration.
    • Allows exporting a virtual table and virtual views to an SCM provider.

    For more information, see Exporting a virtual view to a Software management configuration provider.

  • Runstats function collects statistics about the data that is stored in the target database table.

    For more information, see Runstats function.

  • Viewing online documentation for SMF virtual tables for the following without having to visit the IBM website:
    • SMF virtual tables
    • Columns in the SMF virtual tables
    • SMF sub-tables
    • Columns in SMF sub-tables

    For more information, see Viewing documentation.

  • Installation using IBM z/OS Management Facility (z/OSMF) workflow files.

    For more information, see AVZ installation using z/OSMF workflow (Automated manner).

  • IDF-Direct lets the DVM SQL engine to be skipped for execution of the queries and to process the queries at the connected DRDA datasource.
  • Create views in Db2 subsystems on Linux environments and to create Db2 federation nicknames with DVM Studio.

    For more information, see Db2 federation nicknames for distributed environment.

  • Schema maps and all the maps related to the schema are now automatically added to a 64-bit storage.

Key features of Data Virtualization Manager

are the key features of Data Virtualization Manager:

  • Universal Db2 support: Applications using Db2 can now seamlessly integrate with any non-Db2 data source with the same ease of functionality.
  • Lower Mainframe TCO: Ability to run up to 99% of its data virtualization processing in zIIP for significantly reduced capacity usage.
  • Landing Zone support: Ability to combine disparate data and make it available to landing zones supporting ETL, Hadoop, analytics, and data quality.
  • Universal application compatibility: Enables read/write access to mainframe data from any application.
  • Wide range of API support: Access data using any industry standard APIs: SQL, JSON, SOAP, REST
  • Wide Architecture support: Provides support for hybrid, on-premise, cloud, Hadoop, and mainframe computing architectures

Key benefits of Data Virtualization Manager

Following is a summary of the key benefits of using Data Virtualization Manager.

Key benefits of Data Virtualization Manager.
Easier access to Mainframe data:
  • Using Data Virtualization Manager you can knit data from multiple, disconnected sources into a single logical data source, making it much easier to connect mainframe data with your distributed applications. For example, live VSAM, ADABAS, IDMS, IMS, DB2 and SMF data can be joined with non-mainframe data.
  • Use mainframe data in place—no mainframe skills required.
  • Developers access data directly using familiar SQL syntax.
  • Easily integrate mainframe data in applications.
 Reduces cost and complexity of ETL data movement:
  • Because of today's data volumes, ETL and data warehousing technologies are struggling to support the requirements of mobile, cloud, and analytics applications. Data Virtualization Manager integrates with existing data architecture as a faster, more cost-effective means of addressing today's data access needs.
  • Data Virtualization Manager uses less mainframe capacity while fetching real-time data for applications.
  • Data Virtualization Manager optimizes existing ETL processes by creating a logical data warehouse.
Reduce business risk through faster identification of threats and operational failures:
  • Unlike other products, Data Virtualization Manager provides immediate access to mainframe SMF data intercepting it in flight while it is being collected and written to the record.
  • With Data Virtualization Manager, the SMF data is available immediately in a format that can be used for analysis without any mainframe processing costs, so you can address threats before they impact your risk profile or affect operations.
 Accelerate digital transformation:
  • Data Virtualization Manager provides the real-time data essential to exploit new digital technologies, such as web, mobile, cloud, and real-time analytics.
  • Data virtualization masks the underlying mainframe data implementations from the application developer, making it easy to expose mainframe assets as APIs that developers can use to incorporate data and transactions into mobile and cloud applications.
Empower sales with enhanced customer insight:

Data Virtualization Manager lets you enrich your understanding of your customers with real-time data from your mainframe:

  • You can get a single view of the customer by combining data sources from across your enterprise virtually. No more waiting on batch jobs or data-loading into a data warehouse.
  • You can combine mainframe data with location, social media, and other distributed data.
  • You can feed predictive analytics with real-time data to deliver highly targeted offers.
  • You can generate unified dashboards with comprehensive customer data.