We recently explored Ibis, a Python library designed to simplify working with data across multiple storage systems and processing engines. It provides a DataFrame-like API, similar to Pandas, but translates Python operations into backend-specific queries. This allows it to work with SQL databases, analytical engines like BigQuery and DuckDB, and even in-memory tools like Pandas. By acting as a middle layer, Ibis addresses challenges like fragmented storage, scalability, and redundant logic, enabling a more consistent and efficient approach to multi-backend data workflows. Wrote up some learnings
