SAG Natural

Our Natural Rehosting solution combines the industry’s best software platform with proven application consolidation and data migration services. This ensures your entire mainframe estate is deployed to the target environment in the languages and database models you need.

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Eliminate mainframe and licensing costs without changing your Natural syntax

42 minutes

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Why modernise?


Exorbitant costs

Mainframes cost as much as 4,500 percent more to operate than equivalent Cloud counterparts. This figure is compounded by a scarcity of development resources and rising  licensing and maintenance fees for ancillary mainframe utilities, applications, and databases. 

Limited data accessibility

Legacy databases are difficult to integrate with systems on modern platforms. This is because of inherent inextensibility, incompatibility, and rigidity of the underlying hardware and software powering these legacy systems.

Limited flexibility

Companies are rapidly moving to DevOps and the Cloud while consolidating their technology stacks to maximise IT performance. Unfortunately, the inflexibility of mainframes has become a growing hindrance to modern, continuously evolving, agile business.

Natural Rehosting


You can retain your Natural code as-is while taking advantage of the cost savings and infinite elasticity of the Cloud by rehosting your legacy estate with Advanced.

Rehosting, sometimes referred to as replatforming, is ideal for companies whose applications are still meeting their business needs, and who therefore wish to retain their Natural development skills while moving away from non-relational databases and expensive mainframe infrastructure. With rehosting, Natural is migrated onto modern, distributed platforms, either on-premises or in the Cloud, without change. Underlying legacy databases are migrated to relational models, configured to seamlessly interact with your applications via the rehosting platform.

Our Natural Rehosting solution leverages our robust Application Transparency Platform (ATP) rehosting software. ATP is a Natural rehosting and Adabas migration solution that provides an end-to-end strategic pathway for lower licensing costs, higher productivity, and full preservation of legacy assets and business rules. Organisations looking to move away from Natural can use ATP to automatically convert syntax to COBOL, Java, or C# on demand. As an alternative to the re-engineering and conversion solutions available for Natural and Adabas, ATP dramatically reduces the timeframe for the replacement cycle and accelerates your return on investment.

ATP enables automated Adabas migration into the relational database of your choice, processing Natural applications using ATP Language (ATPL). ATP powers Natural rehosting seamlessly from the mainframe environment to a more economical and more robust ATP environment, thus reducing maintenance / licensing fees and mainframe workload. Since ATP interprets and executes each Natural command, the Natural applications can execute against the new relational database without changes to the Natural syntax.

Our eavJES batch execution suite, an ancillary toolset within the ATP rehosting environment, provides a job execution system for organisations who want to preserve their JCL and PROCS, and continue to maintain them even when they move off the mainframe.

In addition, ATP includes a full-featured UI-based development platform that includes Natural code analysis, flow diagramming, impact analysis, pattern matching, version comparison, and interactive debugging. The existing Natural development team can continue to develop and maintain applications as they always have with the support of modern development tools.

Retaining Natural syntax may be the final modernisation goal for some organisations. For others, it might be a step in a phased approach to move away from procedural code and pre-relational databases altogether. ATP is designed to support customers regardless of how far down the modernisation path their migration effort takes them. For migrations away from Natural, ATP supports automated refactoring to C#, Java, or COBOL through a simple right-click, SaveAs function. This is an industry first, bringing automated refactoring to the end user. Using this feature, it is possible to maintain the Natural, but choose to have the actual syntax converted to C#, Java, or COBOL at the time the syntax is saved by the developer. Once saved, the newly converted code is functionally equivalent to the legacy Natural syntax. This feature enables the best of both worlds; re-use of developers’ existing skill sets in Natural and their extensive knowledge of the applications, while deploying as C#, Java, or COBOL.

Learn more

Over 35 years of Natural and 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


  • Eliminate mainframe and licensing costs without changing your Natural syntax

    By joining this webinar you will discover how to retain Natural Syntax, eliminate the mainframe, and chart a course for cloud readiness.

    Watch on demand
    an image associated withEliminate mainframe and licensing costs without changing your Natural syntax Webinar
  • Avoiding Natural Disaster

    This whitepaper outlines how a phased approach to modernisation removes the common risks and reasons to stay with outdated technology.

    Read whitepaper
    an image associated withAvoiding Natural Disaster Whitepaper
  • 2021 Mainframe Modernisation Report

    Report Read report
  • US Department of Energy I Government

    Tools Read case study
  • Rehosting mainframe applications

    Webinar Watch on demand
  • Natural and Adabas migration: mitigating disaster with the power of automation

    Blog Read blog

News & Opinions

BLOG // 02-12-2021

Old Data vs. Big Data: Data Management and Legacy Systems

by Rob Anderson, Vice President of Marketing and Product for Application Modernization

Old Data vs. Big Data: Data Management and Legacy Systems