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After years of promising an open lakehouse, Apache Iceberg with REST catalogs plus dbt on top has jelled in 2025 into the reference stack. I break down what it solves, where it still hurts, and why the clean split between table, engine and transformation matters more than it looks.
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.
DuckDB is an embedded, columnar, vectorized SQL engine that runs inside your own process and queries Parquet, CSV, JSON, S3, and URLs in place. For DuckDB analytics up to a hundred gigabytes it beats pandas on speed and a cloud warehouse on friction cost. It is not a transactional engine. Version 1.0 landed in June 2024.
