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DuckDB has spent two or three years quietly working its way into data architectures. It is no longer just the embedded database for local analytics: in 2025 it keeps turning up in concrete enterprise cases where it replaces far pricier pieces. A tour of the real patterns.
Open table formats over data lakes have moved from curiosity to backbone of many analytics architectures. Delta Lake 4.0 and Apache Iceberg 1.9 are the two with the most weight in 2025. We review where each one stands and which criteria make sense when choosing between them.
Polars runs 3 to 10 times faster than pandas on aggregations, joins, and filters over parquet datasets of 1 to 20 GB, and holds 40 to 60 percent less memory thanks to native Arrow columns. With the 1.x API frozen and Arrow interoperability, both libraries can coexist in one pipeline.
