Cloud Data Migration

Our Automated Data Migration solution delivers modern Cloud-enabled databases and supporting applications that are functionally equivalent to their legacy counterparts. Our software converts the non-relational database into a relational database, providing instant access to vendor and third party tools for reporting, monitoring, maintaining, and documenting. In addition, it allows the data to be accessed and analysed by a vast talent pool of DBAs with modern skillsets.

Our solutionResourcesRegister an interest

Your Salvation is Automation: Leverage your post-modernisation automation

Webinar | 30 minutes

Watch on demand

Why modernise?


Scarcity of domain expertise

Developers and database administrators who understand mainframe technology are reaching retirement age and no one is trained to replace them, resulting in a steadily diminishing talent pool. As this shortage grows, the costs and risk of relying on legacy systems will continue to rise.

Limited flexibility

Successful digital transformation and business agility hinges on good data. Non-relational databases and the underlying assets that support them were not designed for today’s business demands or modern IT, resulting in difficult integrations, inaccessible data, and limited flexibility.

Exorbitant costs

Mainframes cost as much as 4,500 per cent more to operate than equivalent Cloud counterparts. This figure is compounded by rising licensing and maintenance fees for ancillary mainframe applications and databases.

Automated Data Migration


Our Automated Data Migration software converts your non-relational database into a relational database, providing instant access to vendor and third party tools for reporting, monitoring, maintaining, and documenting. In addition, it allows the data to be accessed and analysed by the vast talent pool of DBAs with modern skillsets.

Automated Data Migration options include:

  • Adabas to relational (Oracle, Db2, SQL Server, or PostgreSQL)
  • IDMS and IDMSX to relational
  • IMS to relational
  • VSAM to relational
  • Db2 to an alternative relational model

Automated Data Migration consists of data and database conversion, as well as Automated Refactoring of applications used to access the in-scope data. Database and data conversion is typically performed simultaneously with the application refactoring activities, although they can be performed independently.

Automated Refactoring of ancillary applications

Automated Refactoring transforms the applications that use the in-scope data and databases to object-oriented Java or C# for deployment to the Cloud or in open systems on premises. We can also consolidate the application codebase associated with the data migration by refactoring it to COBOL for on-mainframe deployments.

Automated Data Migration activities

Database and data conversion includes de-construction of the database definitions into metadata artifacts. We tune our Automated Data Migration software to accommodate any additional conversion or architectural rules based upon assess and design phase findings and your feedback. This can include column and table naming, date type formats, overrides for redefines and group level clauses, and preferences for each statement and clause in the resulting DDL.

With our data migration experts at the helm, the Automated Data Migration software generates a brand new DDL which defines a complete relational database, providing the same data access, features, and unique functionality as the legacy database.

The resulting relational database definitions are tested by our data migration experts prior to delivery to your team to ensure that the generated code is syntactically correct. Retention of functionality is an important consideration when evaluating data migration solutions. Fortunately, we provide a complete replacement for all database and application functionality and unique constructs by default. For example, primary keys, foreign keys, and index definitions are automatically created, and all constraints are generated into the resulting DDL. Table spaces, indexes, table names, and column names are all generated according to customer naming standards as well. For mainframe-to-mainframe migrations, we even deliver the JCL required to compile and execute the extracts from the legacy database. Workbenches for date type handling also enable the new databases and applications to take advantage of all the date and time data types in the relational database.

The legacy database definition can be re-collected and processed through our Automated Data Migration software anytime throughout the project lifecycle. This prevents the need to put a freeze on changes to the legacy database structure, a huge win for critical business systems that change often.

Learn more

Over 35 years of mainframe modernisation experience

More than 500 successful modernisation projects completed

Over 2.5 billion lines of code refactored through automation

Intelligent modernisation, unparalleled experience


Additional insights to help you modernise


  • UK Government Agency

    Faced with Fujitsu mainframe renewal deadline, we successfully refactored IDMSX database to Microsoft Azure Public Cloud.

    Read case study
    an image associated withUK Government Agency Tools
  • Liberate legacy data

    This whitepaper provides insight to the common challenges in handling legacy data and options for solving them.

    Read whitepaper
    an image associated withLiberate legacy data Whitepaper
  • 2021 Mainframe Modernisation Report

    Report Read report
  • Desjardins I Financial Services

    Tools Read case study
  • Live Discussion: The 2021 Mainframe Modernisation Business Barometer Report

    Webinar Watch on demand
  • Dwr Cymru Welsh Water I Utilities

    Tools Read case study

News & Opinions

BLOG // 13-02-2024

How DevOps is influencing mainframe modernisation strategies

by Tim Jones, Managing Director - Application Modernisation

How DevOps is influencing mainframe modernisation strategies