7 comments

  • kipukun 3 hours ago
    The cuDF interop in the roadmap [1] will be huge for my workloads. XGBoost has the fastest inference time on GPUs, so a fast path straight from these Vortex files to GPU memory seems promising.

    [1] https://github.com/vortex-data/vortex/issues/2116

  • meehai 1 hour ago
    Can you append new columns to a file stored on disk without reading it all in mempey? Somehoe this is beyond parquet capabilities.
  • rubenvanwyk 1 hour ago
    Vortex and Lance both seem really cool but will have to infiltrate either the Delta or Iceberg specs to become mainstream.
  • xigoi 2 hours ago
    Can we stop with the cringe emojis at the start of every heading?
  • nahnahno 5 hours ago
    how does this compare to Arrow IPC / Feather v2?
    • rubenvanwyk 1 hour ago
      I've never understood why people say Feather file format isn't meant for "long-term" storage and prefer Parquet for that. Access is much faster from Feather, compression better with Parquet but Feather is really good.
      • sheepscreek 33 minutes ago
        Honestly I think Arrow makes Feather redundant. To answer your question, Parquet is optimized for storage on disk - can store with compression to take leas space, and might include clever tricks or some form of indices to query data from the file. Feather on the other hand is optimized for loading onto memory. It uses the same representation on disk as it does in memory. Very little in the way of compression (if any). No optimized for disk at all. BUT you can memory map a Feather file and randomly access any part of it in O(1) time (I believe, but do your own due diligence :)
  • sys13 7 hours ago
    How does this compare with delta lake and iceberg?
    • oa335 7 hours ago
      Vortex is a file format, where as delta lake and iceberg are table formats. it should be compared to Parquet rather than delta lake and iceberg. This guest lecture by a maintainer of Vortex provides a good overview of the file format, motivations for its creation and its key features.

      https://www.youtube.com/watch?v=zyn_T5uragA

      • ks2048 6 hours ago
        The website could use a comparison / motivation in comparison to Parquet (beyond just stating it's 100x better).
        • 3eb7988a1663 4 hours ago
          Agreed, really need a tl;dr here, because Parquet is boring technology. Going to require quite the sales pitch to move. At minimum, I assume it will be years before I could expect native integration in pandas/polars/etc which would make it low effort enough to consider.

          Parquet is ..fine, I guess. It is good enough. Why invoke churn? Sell me on the vision.

          • frisbm 3 hours ago
            DuckDB just added support for vortex in their last release using the Vortex Python package so hopefully other tools wont be too far behind
          • bsder 1 hour ago
            > Going to require quite the sales pitch to move.

            Mutability would be one such pitch I would like to see ...

      • sys13 7 hours ago
        I think it would still make sense to compare with those table formats, or is the idea that you would only use this if you could not use a table format?
        • bz_bz_bz 6 hours ago
          That’s like comparing words with characters.

          Vortex is, roughly, how you save data to files and Iceberg is the database-like manager of those files. You’ll soon be able to run Iceberg using Vortex because they are complementary, not competing, technologies.

    • cpard 6 hours ago
      As others said, Vortex is complementary to the table Formats you mentioned.

      There are other formats though that it can be compared to.

      The Lance columnar format is one: https://github.com/lancedb/lancedb

      And Nimble from Meta is another: https://github.com/facebookincubator/nimble

      Parquet is so core to data infra and widespread, that removing it from its throne is a really really hard task.

      The people behind these projects that are willing to try and do this, have my total respect.