Michele Simionato - How to migrate from PostgreSQL to HDF5 and live happily ever after This talk is for people who have a lot of floating numbers inside PostgreSQL tables. I will bring as an example my personal experience with a scientific project that used PostgreSQL as storage for a rather complex set of composite multidimensional arrays and ran into all sorts of performances issues, both in reading and writing the data. I will explain how I solved all that by dropping the database in favor of an HDF5 file, while keeping the application running and the users happy. ----- This talk is for people who have a lot of floating numbers inside PostgreSQL tables and have problems with that. I will narrate my experience with a scientific project that used PostgreSQL as storage for a rather complex set of composite multidimensional arrays and ran into all sorts of performances issues, both in reading and writing the data. I will discuss the issues and the approach that was taken first to mitigate them (unsuccessfully) and then to remove them (successfully) by a complete rethinking of the underlying architecture and eventually the removal of the database. I will talk about the migration strategies that were employed in the transition period and how to live with a mixed environment of metadata in PostgreSQL and data in an HDF5 file. I will also talk about concurrency, since the underlying application is distributed and massively parallel, and still it uses the purely sequential version of HDF5. Questions from the audience are expected and welcome. The talk is of interest to a large public, since it is mostly about measuring things, monitoring and testing a legacy system, making sure that the changes do not break the previous behavior and keeping the users happy, while internally rewriting all of the original code. And doing that in a small enough number of years!