2026-11-07 –, Track 05 Language: Español
Apache Arrow and Apache Parquet are the de-facto standards for in-memory and file formats for columnar data. We use them on our data workflows daily, sometimes even without noticing. This talk will demystify these formats by going over the specifications and showing some real world examples of how the data actually looks on our systems.
For Arrow, we will briefly mention some of the batteries included for exchanging data like Arrow IPC, Arrow Flight or Arrow ADBC and how they relate to the core In-memory format.
The main libraries shown will be PyArrow with its Arrow and Parquet implementation and datanomy a new tool created for visualizing data formats.
Raúl Cumplido is an Apache Arrow committer and PMC member, currently working as a Scientific Software Engineer at QuantStack and an Associate Professor at Universitat de Barcelona. Has contributed to several projects on the data ecosystem like Apache Parquet and Apache Iceberg.
Started working with Python in 2008 with Python 2.5 and has been involved in the Python Spanish Association, being secretary in the past and one of its co-founders. He is usually active sharing what is Apache Arrow, Parquet and Iceberg.