These two platforms allow to easily store and manipulate distributed data from object-oriented applications, enabling programmers to handle object persistence using the same classes they use in their programs, thus avoiding time consuming transformations between persistent and non-persistent data models. Also, Hecuba and dataClay enable programmers to transparently manage distributed data, without worrying about its location. This is achieved by adding a minimal set of annotations in the classes.

Both Hecuba and dataClay can work independently or integrated with the COMPSs programming model and runtime to facilitate parallelization of applications that handle persistent data, thus providing a comprehensive mechanism that enables the efficient usage of persistent storage solutions from distributed programming environments.

Both platforms offer a common interface to the application developer that facilitates using one solution or the other depending on the needs, without changing the application code. Also, both of them have additional features that allow the programmer to take advantage of their particularities.

Type of methodology: Combination of lecture and hands-on

Participants receive the certificate of attendance: Yes

Paid training activity for participants: No, it's free of charge

Participants prerequisite knowledge: Basic programming skills in Python and Java.

Previous attendance to PATC course on programming distributed systems with COMPSs is recommended.