Plenty. Beyond the lightning speed and great compression, DuckDB's SQL dialect has ergonomics standard SQL simply does not have - it is closer to Python, SQL and compression in one box. A sampler:
SELECT * EXCLUDE (col1, col2) - everything except named columns. Prefix-aliasing - total: price * qty instead of price * qty AS total, reads left-to-right. Reusable aliases - define an alias in SELECT and use it in WHERE / GROUP BY / ORDER BY instead of repeating the expression. LIMIT 10% instead of a row count. QUALIFY - filter on window functions directly, no nested subquery. GROUP BY ALL / ORDER BY ALL. List comprehensions ([x*2 FOR x IN scores IF x > 70]) and lambdas (list_filter(arr, x -> x > 10)). Dot-operator chaining (price.CAST(FLOAT).ROUND(2)). Glob patterns (SELECT * FROM 'logs/*.csv') and direct file queries (SELECT * FROM 'data.parquet') with no CREATE TABLE.
Overview: https://www.tigzig.com/post/duckdb-isn-t-just-fast-sql-it-s-python-sql-and-compression-all-in-one-box (which credits Jasja De Vries's 30-day DuckDB series). Related: can DuckDB handle a 16GB dataset with no server https://www.tigzig.com/agents-faq/can-duckdb-handle-a-16gb-dataset-no-server and how to convert a CSV to a DuckDB database https://www.tigzig.com/agents-faq/how-to-convert-csv-to-a-duckdb-database.
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