Sharath Sadashivan
VP of Solutions Delivery

Nick Wilbourn
Technical Writer

Leveraging Data Virtualization in Support of Database Migration

Data Virtualization (DV) may be one of the most misunderstood concepts in data management today. While some view it simply as a means of data integration or as an alternative to Extract, Transform, Load (ETL), DV offers value across several applications. In database migration, for example, DV provides cost savings, reduced migration time, and increased flexibility.

By decoupling data consumers from data producers and data stores, DV separates the process of database migration from application modernization. This frees applications from being tied to specific database technologies, meaning migration can occur without time-consuming, costly code rewrites to match the new cloud platform’s language / dialect. In this regard, DV lowers the barrier to entry for organizations considering cloud migration. By mitigating some of the major risks associated with database migration, DV solutions allow organizations to migrate confidently and enjoy the scalability and affordability offered by cloud platforms. The Multiplatform Data Acquisition, Collection, and Analytics (MDACA) product suite offers a robust DV solution.

MDACA Big Data Virtualization

MDACA Big Data Virtualization (BDV) is designed to provide a single view of enterprise data and simplify the technical complexities of database types, data locations, and data transformations for business owners. MDACA BDV provides a logical data layer that integrates enterprise-wide data across disparate systems and manages the unified data within a single location for centralized data access. MDACA BDV provides virtual data access that supports the integration of multiple data sources with ETL tools such as MDACA Data Flow. Figure 1 demonstrates a conceptual model of MDACA BDV.

MDACA BDV provides several key benefits, including the following:

  • Supports data queries across multiple systems while simultaneously mitigating data replication, thereby bolstering master data.
  • Supports Massively Parallel Processing (MPP), allowing data queries to execute multiple operations simultaneously, via several processing units, to achieve high performance.
  • Achieves cost reduction via management and legacy data migration initiatives.
  • Optimizes operations in both Amazon Web Services (AWS) and Azure clouds.
  • Offers comprehensive data abstraction, federation, integration, and transformation.
  • Enables integration of data from multiple sources into reusable, unified logical data models.
  • Minimizes data movement and number of data stores by leveraging logical data access.
  • Reduces data replication, storage, and hardware costs.
  • Leverages federated queries, eliminating the need for database consolidation and movement.
  • Is accessible through standard Structured Query Language (SQL) and/or web services interfaces for virtual data utilization and sharing.
  • Provides centralized security administration to manage all security tasks in a central User Interface (UI) or via web services Application Programming Interfaces (APIs).
  • Offers enhanced support for various authorization methods, including Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC), etc.
  • Centralizes auditing of user access and administrative actions for increased security.

Database Migration Using MDACA BDV

In any organization that leverages big data technologies, the data and supporting infrastructure are constantly evolving through iterative stages of consolidation and migration. As back-end systems continue to adapt at an unprecedented rate, organizations are challenged to address key questions such as the following:

  • How are front-end systems and users reliant on data for everyday use impacted by modernization efforts?
  • What proactive planning measures need to be addressed in order to minimize changes?

By introducing the MDACA BDV layer, infrastructure changes and data migration challenges are mitigated by reducing the impact on front-end users accessing the data. Teams responsible for the migration can develop a strategy that allows the transition of the data source at the MDACA BDV layer, while developing plans to minimize costs and increase team productivity. Figure 2 illustrates how MDACA BDV integrates data virtualization into cloud and database migration.


Data virtualization offers clear benefits for organizations considering database migration, including migration to the cloud. Virtualization enables enterprises to migrate from on-premises to the cloud in roughly one-tenth the time it takes for a conventional cloud migration, with significant cost savings and risk reduction. MDACA BDV is a proven virtualization solution that provides a single view of enterprise data while simplifying the technical complexities associated with cloud migration.

MDACA BDV is available on the AWS Marketplace as part of the MDACA product suite.