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

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 in 2016 by a team of interdisciplinary experts with vast experience from world leading research facilities (such as CERN), Fortune 50, and top universities in the United States and Europe. We believe (scientific) big data management should be simple, clean and fast, and we’re especially passionate about the promises of machine learning in cleantech, healthtech and science.

HDFql is currently being used to power electric vehicle strategies, to crunch data in renewable energy, and to deliver breakthroughs in science, biotechnology and engineering. Because we aspire to advance data-driven discoveries, HDFql is free.