Fredrik has Matt Topol and Lars Wikman over for a deep and wide chat about Apache Arrow and many, many topics in the orbit of the language-independent columnar memory format for flat and hierarchical data. What does that even mean? What is the point? And why does Arrow only feel more and more interesting and useful the more you think about deeply integrating it into your systems? Feeding data to systems fast enough is a problem which is focused on much less than it ought to be. With Arrow you can send data over the network, process it on the CPU - or GPU for that matter- and send it along to the database. All without parsing, transformation, or copies unless absolutely necessary. Thank you Cloudnet for sponsoring our VPS! Comments, questions or tips? We are @kodsnack, @tobiashieta, @oferlund and @bjoreman on Twitter, have a page on Facebook and can be emailed at info@kodsnack.se if you want to write longer. We read everything we receive. If you enjoy Kodsnack we would love a review in iTunes! You can also support the podcast by buying us a coffee (or two!) through Ko-fi. Links Lars Matt Øredev Matt’s Øredev presentations: State of the Apache Arrow ecosystem: How your project can leverage Arrow! and Leveraging Apache Arrow for ML workflows Kallbadhuset Apache Arrow Lars talks about his Arrow rabbit hole in Regular programming SIMD/vectorization Spark Explorer - builds on Polars Null bitmap Zeromq Airbyte Arrow flight Dremio Arrow flight SQL Influxdb Arrow flight RPC Kafka Pulsar Opentelemetry Arrow IPC format - also known as Feather ADBC - Arrow database connectivity ODBC and