HDFql is the first high-level (declarative) language to manage HDF5 data. Designed to be as simple and powerful as SQL, it dramatically reduces the learning effort and time needed to handle HDF5. Built on intuitive syntax, HDFql offers a clean interface which reads and writes HDF5 data across programming languages and platforms.

Not only that, HDFql is so easy that even first time users instantly get it. Because it is based on natural language, you just tell HDFql what to do. This is in stark contrast to other APIs, which require users to specify all the intricate details of how to handle HDF5. That is how HDFql enables users to go from 19 lines of highly complex code to just 2 lines of simple code.

As an example, imagine that you need to create an HDF5 file named “my_file.h5” and, inside it, a group named “my_group” containing a one dimensional (size 3) dataset named “my_dataset” of data type integer. Additionally, the dataset is compressed using ZLIB and initialized with values 4, 8 and 6. In HDFql, this can easily be implemented as follows:

In contrast, using the C API on the same example is quite cumbersome:

HDFql was launched by a team of interdisciplinary experts with vast experience from CERN, global Fortune 50 industry and world-renowned research facilities. We believe managing (scientific) data should be simple and fast, and we’re especially passionate about the promises of machine learning in cleantech, healthtech and science.