cofin/duckdb

DuckDB

Overview

DuckDB is an in-process analytical database with rich SQL dialect, first-class support for Parquet/CSV/JSON, and client APIs for Python, Node.js, Rust, Java, R, Go, WASM, and more. It excels at OLAP workloads, local data exploration, embedded analytics, and data engineering pipelines across local and cloud data sources.

References Index

For detailed guides and patterns, refer to the following documents in references/:

• Core DuckDB
  • SQL dialect highlights, data import/export, configuration, and key SQL patterns.
• Advanced SQL Patterns
  • QUALIFY, COLUMNS(*), EXCLUDE/REPLACE/RENAME, list comprehensions, structs, maps, PIVOT/UNPIVOT, ASOF joins, UNION BY NAME, recursive CTEs, GROUP BY ALL, SAMPLE, string slicing, lambda functions.
• Performance Tuning
  • EXPLAIN ANALYZE, storage inspection, pushdown optimizations, parallel execution, memory management, Parquet performance, partition pruning, bulk loading, indexing.
• Data Engineering
  • Multi-source reads (CSV, Parquet, JSON, Excel, SQLite, PostgreSQL, MySQL), httpfs/S3/GCS/Azure, glob patterns, Delta Lake, Iceberg, partitioned output, ETL patterns, cross-database queries, secrets management.
• Python Client
  • Connection management, DataFrame integration, relational API, and parameter binding.
• Client Connections
  • Node.js, Rust, Java/JDBC, R/dbplyr, Go, WASM, ADBC (Arrow), ODBC driver setup and usage.
• Key Function Reference
  • Aggregates, date/time, string, list, struct, map, spatial, and full-text search functions.
• Extension Development
  • Building, testing, and distributing DuckDB C++ extensions.
• CLI
  • Interactive shell usage, dot-commands, and scripting patterns.
• Configuration & Administration
  • Pragmas, SET statements, database files/WAL/checkpointing, catalog inspection, extension management, cloud credentials, .duckdbrc startup config.

---

<workflow>

Key SQL Dialect Features

• SELECT * EXCLUDE (col) -- select all columns except specific ones
• SELECT COLUMNS('pattern') -- select columns matching a regex
• PIVOT / UNPIVOT -- built-in pivot support
• LIST, STRUCT, MAP nested types with full query support
• GROUP BY ALL, ORDER BY ALL -- automatic grouping/ordering
• Friendly SQL: FROM tbl SELECT col syntax, implicit SELECT *

</workflow>

---

Quick Start

<example>

import duckdb
con = duckdb.connect()  # in-memory
result = con.sql("SELECT 42 AS answer").fetchall()

# CLI
duckdb mydb.duckdb "SELECT * FROM read_parquet('data/*.parquet')"

</example>

---

Official References

• DuckDB documentation: https://duckdb.org/docs/
• Python API: https://duckdb.org/docs/api/python/overview
• Extensions: https://duckdb.org/docs/extensions/overview
• CLI: https://duckdb.org/docs/api/cli/overview
• Extension template: https://github.com/duckdb/extension-template

Shared Styleguide Baseline

• Use shared styleguides for generic language/framework rules to reduce duplication in this skill.
• General Principles
• PostgreSQL
• Keep this skill focused on tool-specific workflows, edge cases, and integration details.

<guardrails> ## Guardrails

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<validation> ## Validation

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