Seems like the problem here is there is several high quality and well-developed formats, but the author and the commenters here dismiss them because of the different trade-offs they make.
csv -- Simple for simple use cases, text-based, however many edge cases, feature lacking etc
xlsx -- Works in excel, ubiquitous format with a standard, however complicated and missing scientific features
sqlite -- Designed for relational data, somewhat ubiquitous, types defined but not enforced
parquet / hdf5 / apache feather / etc -- Designed for scientific use cases, robust, efficient, less ubiquitous
capn proto, prototype buffers, avro, thrift -- Has specific features for data communication between systems
xml -- Useful if you are programming in early 2000s
GDBM, Kyoto Cabinet, etc -- Useful if you are programming in late 1990s
Pick your poison I guess. Engineering is about trade offs.
csv -- Simple for simple use cases, text-based, however many edge cases, feature lacking etc
xlsx -- Works in excel, ubiquitous format with a standard, however complicated and missing scientific features
sqlite -- Designed for relational data, somewhat ubiquitous, types defined but not enforced
parquet / hdf5 / apache feather / etc -- Designed for scientific use cases, robust, efficient, less ubiquitous
capn proto, prototype buffers, avro, thrift -- Has specific features for data communication between systems
xml -- Useful if you are programming in early 2000s
GDBM, Kyoto Cabinet, etc -- Useful if you are programming in late 1990s
Pick your poison I guess. Engineering is about trade offs.