Quantyca Legacy Modernization cases


More and more companies are thinking about modernization strategies for their legacy systems (SAP, Mainframe, custom applications built on Oracle DB, etc.) in order to take advantage of the convenience and scalability of the Cloud without having to face lengthy and risky decommissioning projects for core systems on which they have invested heavily in the past years.

The modernisation of legacy systems is necessitated by the many digital initiatives that push towards a constant growth of touchpoints in multi-channel logic (System of Engagement) and the development of modern AI-based applications (System of Insight).

ChallengesTo carry out these digital transformation initiatives, however, traditional point-to-point batch integrations between legacy systems and new services are not sufficient, as they do not guarantee the necessary scalability, responsiveness and cost-effectiveness.


  • Legacy systems struggle to integrate with an increasing number of external applications due to scalability issues
  • Data is extracted from legacy systems mainly with batch integrations, thus causing constant misalignment between systems
  • The development and maintenance costs of point-to-point integrations between the legacy and target systems are high
  • Finally, multipoint access to legacy systems exposes them to the risk of misuse of data, especially sensitive ones
of IT decision makers
believe that the inflexibility of their legacy systems limits IT's ability to innovate


Changes to the data managed by the source legacy system are intercepted by a Change Data Capture (CDC) system, replicated on a data streaming platform and then redistributed to the target systems.

The CDC reads the transaction log of the legacy system directly, thus allowing any changes to be intercepted in real time and with minimal impact on the source.

The data streaming platform decouples the source legacy system from the target systems, ensuring scalability and durability and avoiding costly point-to-point integrations.

The complete route

1. Legacy offloading
Data extracted from the legacy system are replicated via the streaming platform on target systems that use them for readings
2. Legacy isolation
Frontend applications use the streaming platform not only to read data but also to request execution of commands on the legacy system instead of making direct calls
3. Legacy refactoring
Legacy decoupled from frontend systems for both reads and writes can be refactored with minimal impact on the latter


Less load on backend systems
Faster response times of frontend applications
Greater integration in omnichannel logic between the different touchpoints
Greater agility in adopting new applications and evolving the architecture
Reduction in IT costs related to integration activities
Reduction in risks due to misuse of data
Reduction of impacts on frontend systems due to changes in backend systems

Success stories

Online Webinar
Digital Integration Hub 2021
Date and Time: 07/07/2021

Main topics In this webinar, DIH will be presented as an architectural pattern that can decouple legacy systems from consumers and, at the same time, make data available at various...

Video Talk
Cloud Data Fabric 2021
Date and Time: 20/10/2021

Main Topics In this webinar, we talked about how to create a Data Fabric in the cloud and modern. We talked about the characteristics of this type of architecture, its...

Online Webinar
Data Management Trends 2022
Date and Time: 06/07/2022

Data Management Trends On this page, you can find the “Data Management Trends” presentation by Andrea Gioia, CTO & Partner of Quantyca, originally presented during the Data & Drinks event...



Data Management Trends – Slide Deck


La Data Strategy come motore dell’IT


Il percorso di ammodernamento della Data Platform per abilitare la digital transformation – IKN Forum Retail 2021


I principi di un moderno Data Management


Cloud Data Fabric – Partner Connect – Quantyca, AWS & Qlik

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