Java
All our new products are based on a Java back end – a stable runtime environment and the large number of open source libraries make this platform unbeatable.
Spring
The Spring ecosystem – especially Spring Boot – forms the basis of many of our applications. The many components handle the technical basis, allowing a greater focus on functional implementation.
JavaScript and TypeScript
For in-browser development we rely on the language of the Internet – JavaScript or its new variant, TypeScript. TypeScript allows IDE support via types, without losing the flexibility of JavaScript.
Angular
The basis for the front end of web applications and single-page apps.
C/C++
For some of our back office systems, we rely on the stability of C/C++.
Delphi
For the rapid development of Windows rich clients.
SQL Databases: PostgreSQL and Oracle
Relational databases form the backbone of most of our applications – access is usually via JPA/Hibernate.
ElasticSearch or Apache Solr
For full text search and general searches, for example on Das WeltAuto.
Cypress, Playwright, Selenium
For automated end-to-end tests, we mostly use Cypress or Playwright. Many of our E2E tests are also still based on Selenium.
Jenkins and GitLab CI
The CI/CD pipelines for our applications run on the basis of Jenkins or GitLab CI.
Git/Subversion.
Almost all of our projects use Git as a version management system – only in a few projects do we still rely on Subversion.
IntelliJ IDEA, Visual Studio Code, Visual Studio und Delphi
We make use of a range of IDEs – depending on the project and technology, we use whatever fits best.
OpenShift/Kubernetes
We deploy our cloud-native applications in our private and public cloud based on OpenShift/Kubernetes.
Azure
Azure is our core cloud platform and provides a good basis for our cloud journey.
Python
Machine learning, cloud automation or CMS systems – Python is used by many teams at Porsche Informatik.
Linux Container / Docker
Today, many of our applications are packaged in container images and distributed in the cloud. This allows a high level of team flexibility and guarantees a consistent environment from development to production.
Spark
Spark enables us to run data queries on large data sets from different sources at high speed and good performance, increasing the quality of Big Data analytics applications.
SAP HANA
In the SAP environment, we rely on the HANA database in conjunction with the new applications (BW on HANA and S4 HANA) as future-oriented solutions.