We use cookies to help you navigate efficiently and perform certain functions. You will find detailed information about all cookies under each consent category below.
The cookies that are categorized as "Necessary" are stored on your browser as they are essential for enabling the basic functionalities of the site. ...
Necessary cookies are required to enable the basic features of this site, such as providing secure log-in or adjusting your consent preferences. These cookies do not store any personally identifiable data.
Functional cookies help perform certain functionalities like sharing the content of the website on social media platforms, collecting feedback, and other third-party features.
Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as the number of visitors, bounce rate, traffic source, etc.
Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.
Advertisement cookies are used to provide visitors with customized advertisements based on the pages you visited previously and to analyze the effectiveness of the ad campaigns.
DXL
DoorsNG
Webflux
Java
Mongo DB
Our client is a Swiss company selling IT products
We were tasked with creation of a solution for transferring data from IBM Doors classic to the new generation, which encompasses a different data model.
The project employs an unconventional approach to the issue, to the extent that even a seasoned expert in the field remained speechless for a moment when confronted with our solution. The core component of this tool is written in Java, and it leverages a range of technologies, including DXL, JSON, and MongoDB. Functionally, the tool is divided into three distinct phases: download, transformation, and upload.
Our tool, designed to migrate data seamlessly from legacy IBM systems to next-generation platforms, is showcasing its prowess. It successfully handles substantial data loads, with samples reaching several terabytes in size, highlighting its robustness and scalability. This tool represents a crucial bridge between legacy and modern systems, enabling the seamless transfer of vital data. Its architecture, ensures flexibility and scalability in handling diverse data types. The three-phase approach ensures data integrity and consistency throughout the migration process, ultimately benefiting our client's data management needs.