DuckDB CSV Query — Query CSV Files with DuckDB SQL

DuckDB’s CSV reader is exceptional — it auto-detects delimiters, headers, and types, then lets you query the file with full analytical SQL. PondPilot brings this to your browser with zero setup.

DuckDB’s CSV Superpowers

DuckDB doesn’t just read CSVs — it understands them:

  • Auto-detection: Delimiters, quote characters, headers, and column types are inferred automatically
  • Fast parsing: DuckDB’s CSV reader is significantly faster than Python’s csv module or pandas
  • SQL-native: No loading step — reference the CSV file directly in your SQL
SELECT * FROM 'sales_data.csv' WHERE revenue > 10000 LIMIT 100;

Why DuckDB for CSVs?

vs. pandas: No Python environment needed. DuckDB SQL is often more readable than pandas method chains for analytical queries.

vs. Excel: Handles millions of rows without crashing. SQL is more reproducible than point-and-click formulas.

vs. SQLite: DuckDB is columnar and optimized for analytical queries. Aggregations on large CSVs are dramatically faster.

Multi-CSV Queries

Open several CSVs in PondPilot and join them:

SELECT o.order_id, o.total, c.name, c.segment
FROM orders.csv o
JOIN customers.csv c ON o.customer_id = c.id
WHERE c.segment = 'Enterprise';

DuckDB treats each file as a table. No CREATE TABLE, no LOAD DATA — just reference the filename.

Handle Messy CSVs

Real-world CSVs are messy. DuckDB handles:

  • Mixed delimiters (comma, tab, pipe, semicolon)
  • Quoted fields with embedded newlines
  • Different date formats
  • UTF-8 and other encodings
  • Files with or without headers

Export Results

Query results can be exported back to CSV. Clean up messy data with SQL, then export a polished version.

Try It

Open PondPilot, drop a CSV, and experience DuckDB’s CSV handling firsthand.

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