The Hierarchical Data Format (HDF5) is a open-source, cross-platform, data storage solution originally developed at the National Center for Supercomputing Applications (NCSA) for storage of scientific data and descriptive meta-data in an organised heirarchy. This project extends the power of HDF5 to LabVIEW, which is potentially very useful in many applications.

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This project provides HDF5 v1.8.13+ (released May 2014) functionality to LabVIEW 2010 or newer, and is available as a self-installing package (*.vip file), installable through the VI Package Manager, or directly from the repository.
News alert: As of v2.8.0, h5labview requires HDF5 v1.8.13
To demonstrate how easy it is to use h5labview, here's an example showing creation of a new HDF5 file and writing a dataset with an attribute inside a nested group. A screenshot from HDFView showing the hierarchy of the generated file and the dataset is shown to the right.
As of version 2, h5labview supports compound datatypes (clusters) with "table" access, as demonstrated below.
The table below lists the datatypes supported by h5labview in version 2, and their state of implementation. See this FAQ entry on why not all types are planned to be supported.
LabVIEW typeHDF typeNotes
I8..I64H5T_NATIVE_INT8 .. H5T_NATIVE_INT64Native-endian numerical formats
U8..U64H5T_NATIVE_UINT8 .. H5T_NATIVE_UINT64
SGL, DBLH5T_NATIVE_FLOAT, H5T_NATIVE_DOUBLE
CSG, CDBH5T_COMPOUNDCompound with "real" and "imag" components
EXT, CEXCustom H5T_FLOATHost-compatible extended precision type1
StringH5T_STRINGBoth variable and fixed strings2
BooleanH5T_ENUMEnumeration of "false"=0 and "true"=1
ClustersH5T_COMPOUNDValid clusters may contain any of the above types
ArraysImplemented as dataspaces3Array can be of any dimension of above type, including clusters
EnumsH5T_ENUMLabVIEW enums supported4
ImagesAs per specificationWriting of Grayscale, Truecolor and Palette images supported
WaveformsDatasets of relevant type with attributesIn development
    Notes:
  1. LabVIEW's memory layout for EXT varies across platforms, as does HDF's extended H5T_NATIVE_LDOUBLE. A custom HDF type is created corresponding to the EXT layout on the host machine and HDF performs conversions automatically. This should lead to no precision loss when writing, and enables reading at the greatest precision of the host. The procedure is detailed in this FAQ entry.
  2. HDF supports two types of strings: fixed and variable length. Variable-length strings are implemented and used by default, but LabVIEW strings that contain the null character (\0) must be written as fixed strings. Whether a string is read/written as fixed or variable is configured in LabVIEW, as described in this FAQ entry.
  3. Arrays are implemented in HDF5 with a separate "dataspace" interface. Although an array datatype does exists, the H5T_ARRAY is inefficient and serves limited purpose. The array datatype therefore will not be implemented, neither will arrays of arrays nor clusters including arrays.
  4. LabVIEW defines enums as a set of contiguous unsigned integers. HDF5 sets no such restriction, so as such any LabVIEW enum can be written to an HDF file but HDF5 enums must be read as (signed) integers.