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As I'm given to understand due to the search of issues in the Feather Github, as well as questions in stackoverflow such as What are the differences between feather and parquet?, the Feather format was not recommended as long term storage due to Apache Arrow versions being 0.x.x, and considered volatile due to the continuous new releases.
My question is, has this situation changed as of the current Apache Arrow's version, 1.0.1? Is Feather considered stable to use as long term storage?
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Feather is a fast, lightweight, and easy-to-use binary file format for storing data frames. It has a few specific design goals: Lightweight, minimal API: make pushing data frames in and out of memory as simple as possible. Language agnostic: Feather files are the same whether written by Python or R code.
Feather files (using the v2 -- default -- format version, not the v1 "legacy" version) are stable starting with Apache Arrow 1.0.
This is the documentation of the Python API of Apache Arrow. Apache Arrow is a development platform for in-memory analytics. It contains a set of technologies that enable big data systems to store, process and move data fast.
Feather files (using the v2 -- default -- format version, not the v1 "legacy" version) are stable starting with Apache Arrow 1.0.0.
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