Hierarchical Data Format (HDF) is a set of file formats (HDF4, HDF5) designed to store and organize large amounts of data.

Utilize the HDF5 high performance data software library and file format to manage, process, and store your heterogeneous data. HDF5 is built for fast I/O processing and storage. What is HDF5 ®? HDF® sup ports n-dimensional datasets and each element in the dataset may itself be a complex object.

HDF5 consists of a file format for storing HDF5 data, a data model for logically organizing and accessing HDF5 data from an application, and the software (libraries, language interfaces, and tools) for working with this format.

Download the Latest Version of HDF5® This download location is intended for new users of HDF5 or those looking for the most recent production version. Older versions of HDF5 can be downloaded from the Support site. Pre-built Binary Distributions

The HDF Group is the developer, maintainer, and steward of HDF5 software. Find more information about The HDF Group, the HDF5 Community, and other HDF5 software projects, tools, and services at The HDF Group's website.

HDF5 is a completely new Hierarchical Data Format product consisting of a data format specification and a supporting library implementation. HDF5 is designed to address some of the limitations of the older HDF product and to address current and anticipated requirements of modern systems and applications. 1

This is the documentation set for HDF5. It includes specifications and documentation of software and tools developed and maintained by The HDF Group. It is impractical to document the entire HDF5 ecosystem in one place, and you should also consult the documentation sets of the many outstanding community projects.

There are several resources for learning about HDF5. The HDF Group provides an on-line HDF5 tutorial, documentation, examples, and videos. There are also tutorials provided by other organizations that are very useful for learning about HDF5.

Hierarchical Data Format 5 (HDF5) is a unique open source technology suite for managing data collections of all sizes and complexity. HDF5 has features of other formats but it can do much more. HDF5 is similar to XML in that HDF5 files are self-describing and allow users to specify complex data relationships and dependencies.

HDF5 lets you store huge amounts of numerical data, and easily manipulate that data from NumPy. For example, you can slice into multi-terabyte datasets stored on disk, as if they were real NumPy arrays.