  Scientific data is often stored in files because of the simplicity they
provide in managing, transferring, and sharing data. These files are typically
structured in a specific arrangement and contain metadata to understand the
structure the data is stored in. There are numerous file formats in use in
various scientific domains that provide abstractions for storing and retrieving
data. With the abundance of file formats aiming to store large amounts of
scientific data quickly and easily, a question that arises is, "Which
scientific file format is best suited for a general use case?" In this study,
we compiled a set of benchmarks for common file operations, i.e., create, open,
read, write, and close, and used the results of these benchmarks to compare
three popular formats: HDF5, netCDF4, and Zarr.
