TileDB does not allow arrays to change size. Appending new data and removing old data along a specific dimension (ex. time) is useful for realtime applications.
Arrow support (data representations of jagged arrays)
Working on nested arrays is a crucial task in most scientific fields. I think TileDB could perfectly leverage its strengths to support the community working in that field: https://youtu.be/jvt4v2LTGK0?t=1366 Working with Data Management in TileDB and Data Wrangling in awkward-array ( https://github.com/scikit-hep/awkward-1.0 ) or other libraries with arrow support would be extremely beneficial workhorse. Any updates on when Arrow will be supported?
clobber mode in from_pandas
i don't want to append or create a new array or explicitly delete the old array. just replace the array (with or without without time travel)
Support axes labels
TileDB should support attaching axes labels (dataframes in their full generality), so that the user can slice the array based on arbitrary axes label predicates.
Add slicing with strides
TileDB should support slicing with strides, which is quite common in numpy and similar tools.
Independent Attribute Writes
"Currently, if your array consists of more than one attributes, TileDB requires you to provide values for all the attributes in each write operation." I'd love to be able to write attributes independently of each other.
Potentially integrate with Kerchunk to support ingesting mixed-shape arrays into a single xarray-dataset, as discussed here: https://forum.tiledb.com/t/dataset-with-mixed-shapes/485/4 Preferably with support for lazy-loading.
It would be cool to have the possibility to combine multiple tiledb arrays in a single logical view. A simple and fast way would be to require the same schema and just combine individual fragments s.t. the latest write wins. A more useful option would be to also allow concatenation of arrays along some dimension. In Dask, this could be exported as a single array with chunks aligned to the dataset borders. Even better, one could include filtering options or joining by keys. See also the discussion in https://github.com/TileDB-Inc/TileDB/issues/1475 .