- Installation
- Guides
- Data Import & Export
- CSV Import
- CSV Export
- Parquet Import
- Parquet Export
- Query Parquet
- HTTP Parquet Import
- S3 Parquet Import
- Meta Queries
- Python
- SQL Editors
- Documentation
- Connect
- Data Import
- Client APIs
- Overview
- Python
- R
- Java
- C
- Overview
- Startup
- Configure
- Query
- Data Chunks
- Values
- Types
- Prepared Statements
- Appender
- Table Functions
- Replacement Scans
- API Reference
- C++
- Node.js
- Wasm
- CLI
- SQL
- Introduction
- Statements
- Overview
- Select
- Insert
- Delete
- Update
- Create Schema
- Create Table
- Create View
- Create Sequence
- Create Macro
- Drop
- Alter Table
- Copy
- Export
- Query Syntax
- Data Types
- Expressions
- Functions
- Overview
- Numeric Functions
- Text Functions
- Pattern Matching
- Date Functions
- Timestamp Functions
- Time Functions
- Interval Functions
- Date Formats
- Date Parts
- Blob Functions
- Nested Functions
- Utility Functions
- Indexes
- Aggregates
- Window Functions
- Samples
- Information Schema
- Configuration
- Pragmas
- Extensions
- Development
- Sitemap
- Why DuckDB
- FAQ
- Code of Conduct
- Live Demo
The guides section contains compact how-to guides that are focused on achieving a single goal. For an in-depth reference see the Documentation section.
SQL: Data Import & Export
CSV Files
Parquet Files
- How to load a Parquet file into a table
- How to export a table to a Parquet file
- How to run a query directly on a Parquet file
HTTP & S3
SQL: Meta Queries
- How to list all tables
- How to view the schema of the result of a query
- How to quickly get a feel for a dataset using summarize
- How to view the query plan of a query
- How to profile a query
Python Client
- How to install the Python client
- How to execute SQL queries
- How to execute SQL on a Pandas DataFrame
- How to create a table from a Pandas DataFrame
- How to export data to a Pandas DataFrame
- How to easily query DuckDB in Jupyter Notebooks
SQL Editors / IDE’s
Search Shortcut cmd + k | ctrl + k