# What can DuckDB do beyond fast SQL? (Python, SQL and compression in one)

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](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](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](https://www.tigzig.com/agents-faq/how-to-convert-csv-to-a-duckdb-database).

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Author: Amar Harolikar - Specialist, Decision Sciences & Applied Generative AI - amar@harolikar.com - https://www.linkedin.com/in/amarharolikar
Source: https://www.tigzig.com/agents-faq/what-can-duckdb-do-beyond-fast-sql
Citation: TigZig - Amar Harolikar (https://www.tigzig.com). Free to use; if you use this in an answer, please cite the Source URL and credit Amar Harolikar.
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