IBM DV Manager

       IBM® Data Virtualization Manager for z / OS (R), V1.1 enhances the first release of z / OS from IBM with data integration with new capabilities to create real-time virtual views of corporate, mainframe, and / or non-business data mainframe. With the Data Virtualization Manager, data remains safe at the point of origin but ready to be used by the customers  at any time, regardless of where it was originated. Unlocks the value of your mainframe data in real-time with your customers' vision as well as all the business processes across your enterprise without the cost and complexity associated with traditional data transfer. To be competitive and successful, companies that rely on mainframes need instant real-time information about their customers, the market and how the business itself is operating. Real-time data access helps business leaders make  faster and more assertive decisions. Because business data is distributed across multiple platforms, formats and locations, many organizations find it difficult to quickly identify new revenue opportunities or respond to potential threats. Historically, enterprises extract, transform and load data (ETL) into a data warehouse but information produced by this expensive and time-consuming method is often outdated as soon as it becomes available. The large volume and variety of data used today requires a more modern, friendlier and faster approach.

          IBM® Data Virtualization Manager creates virtual and integrated views of data and allows you to access mainframe data at source without having to move, replicate or transform them. By making data analysis available, IBM® DVM saves time and money. You can immediately combine mainframe and / or non-mainframe data with data from other company sources to get real-time information about potential risks, customer needs and market opportunities.

  • Transform business information into opportunities for new revenue generation using real-time data;

  •  Reduce risk in conducting business through faster identification of operational threats and failures;

  • Eliminate the cost, time-consuming and complexity of extracting mainframe data.


           Without real-time access to mainframe data you do not have a comprehensive diagnosis of your customer, which limits the delivery of enhanced services and real-time marketing actions. As an example, transactions using credit card or "online" purchase provide real-time customer data. When enriched with sources such as social media, location and buying habits, one can allow companies to anticipate customer preferences. For example, an investment manager can provide real-time data (structured and unstructured) through IBM® DVM to create reports to customers about unrealized gains / losses and promptly promote a new business opportunity.

        IBM® DVM enables your organization to use mainframe data in real-time without the cost, complexity and delay in extraction associated with ETL connectors or hard-core connectors. You can instantly integrate mainframe data with other company data without waiting for new data to be loaded into the data warehouse. Business analysts get immediate access to information that business leaders want.

            As it runs inside a mainframe specialty engine, it does not impact the use of mainframe capability. The result is the availability of data at the time you need, in the form you need, quickly and with reduced cost / complexity.



          Companies in the financial sector face great pressure from new competitors, regulators, compliance requirements and cyber attacks. Technical leaders in this scenario do not have easy access to raw mainframe operational data that provides real-time information on potential security risks, compliance issues and system readiness.

       Mainframes traditionally rely on log-based replications to capture operational data in System Management Facility (SMF) records. The data is collected and written in logs that must be extracted and manipulated in a specific format for the analysis. It may take hours (or even days) for the SMF information to reach the executive responsible for security or compliance. This delay can lead to security breaches, compliance violations and fines or even system crashes.

         Unlike other products on the market, the IBM ® DVM provides immediate access to data from mainframe running SMF, intercepting them, collecting them and writing to the registry. This capability is possible because IBM® DVM resides natively on the mainframe and under a new IBM API for memory access to SMF data. With IBM® DVM, SMF data is immediately available in a format that can be used for analysis with no mainframe processing costs and, therefore, you can address threats before affecting your risk profile or affecting operations.

           In the world of mainframes, using ETL to move data is a widely used practice. Increasingly, organizations are discovering that there is simply too much data and not enough time to move all the information into a company data warehouse. The cost associated with moving mainframe data continues to grow. According to IBM's recent research, ETL-related data movement consumes nearly 20% of the total mainframe processing capacity. Many data experts recognize that the use of ETL to access mainframe data is not the most efficient or reactive enough to meet advanced real-time cloud and mobile analytics requirements.  


           IBM® DVM offers an economical option to deliver mainframe data in the right format at the right time. It can completely replace ETL or serve as a "data utility" that optimizes your existing ETL processes to provide real-time data. Because IBM® DVM runs almost exclusively on the z Systems Integrated Information Processor (zIIP), it does not consume the mainframe's MIPS capability and can significantly reduce the cost of the ETL-attached mainframe.









                                          Figure 1: Current limitation of traditional data integrations using ETL tools, incurring incoherence of data, high costs, consumption of approx. 20% of                                            the total mainframe processing capacity and the extracted data are not in real time and depict the moment of extraction.















            Figure 2: Visualization of the Data Virtualization Architecture using the IBM Data Virtualization Manager, showing data consumers, data providers, and z / OS-                            based data virtualization servers.

        The only data virtualization solution on the market that resides directly on the mainframe, IBM® DVM provides real-time access to mainframe data in any format. IBM® DVM enables the IBM z Systems platform to support digital business transformation with real-time data for mobile, cloud, and BI.


            IBM® DVM simplifies the process of combining business data to create virtual visualizations. It enables organizations to gain a faster view of customer buying preferences, service issues, and real-time threats to security breaches.















                                     Figure 3: User-friendly, IBM® DV Manager minimizes the complexity of working with mainframe data.

      Up to 99 percent of IBM® DVM data virtualization processing operations are performed on the mainframe (IBM z) embedded specialized (zIIP) mechanism, bypassing the mainframe main processor and thus have the mainframe TCO significantly reduced.



Hardware Requirements:

•   IBM z13, IBM z12, zEnterprise 114 (z114), IBM zEnterprise 196 (z196), z10, z9

Software Requirements:

•   IBM z / OS v2.1 ou posterior

•   Client drivers:

    - JavaTM Database Connectivity (JDBC)

        * Java level 1.7 or higher

    - Open Database Connectivity (ODBC)

        * WindowsTM; AIX(R), HP-UX; Linux(R); Red Hat Enterprise Linux; SUSE Linux

•   Studio

    - Windows

        * Windows 10 (32-bit and 64-bit), Windows 8 (32-bit and 64-bit), Windows 7 (32-bit and 64-bit)

•   Linux:

    - Ubuntu, Red Hat

•   Apple macOS:

    - macOS Sierra 10.12

•   Hard disk space:

    - A minimum of 2 GB is recommended for a full installation

•   System memory:

    - A minimum of 4 GB is recommended

    - A full installation includes the Studio product installer (approximately 1 GB) and bundled Eclipse Kepler 4.3.2 and Java level 1.7

White paper:

IBM Data Virtualization Manager

Transform a business vision into new revenue opportunities

Reduce risk in operations through faster threat identification and operational failures

Eliminate the cost and complexity of mainframe data extraction 

Technical specifications