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- Installation
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- Overview
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- DB API
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- Introduction
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- ALTER TABLE
- ALTER VIEW
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- COPY
- CREATE INDEX
- CREATE MACRO
- CREATE SCHEMA
- CREATE SECRET
- CREATE SEQUENCE
- CREATE TABLE
- CREATE VIEW
- CREATE TYPE
- DELETE
- DESCRIBE
- DROP
- EXPORT and IMPORT DATABASE
- INSERT
- PIVOT
- Profiling
- SELECT
- SET / RESET
- SET VARIABLE
- SUMMARIZE
- Transaction Management
- UNPIVOT
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- LOAD / INSTALL
- Query Syntax
- SELECT
- FROM and JOIN
- WHERE
- GROUP BY
- GROUPING SETS
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- LIMIT and OFFSET
- SAMPLE
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- Overview
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- Overview
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- Guides
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- Data Viewers
- Database Integration
- File Formats
- Overview
- CSV Import
- CSV Export
- Directly Reading Files
- Excel Import
- Excel Export
- JSON Import
- JSON Export
- Parquet Import
- Parquet Export
- Querying Parquet Files
- Network and Cloud Storage
- Overview
- HTTP Parquet Import
- S3 Parquet Import
- S3 Parquet Export
- S3 Iceberg Import
- S3 Express One
- GCS Import
- Cloudflare R2 Import
- DuckDB over HTTPS / S3
- Meta Queries
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- EXPLAIN ANALYZE: Profile Queries
- List Tables
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- My Workload Is Slow
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- Import from Pandas
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- Import from Numpy
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- SQL on Arrow
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- Relational API on Pandas
- Multiple Python Threads
- Integration with Ibis
- Integration with Polars
- Using fsspec Filesystems
- SQL Editors
- SQL Features
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- Browse Offline
- Operations Manual
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This page contains installation options for DuckDB. For production use, we recommend the stable release.
Binaries are available for major programming languages and platforms. If there are no pre-packaged binaries available, consider building DuckDB from source.
Version
-
Stable release (v1.1.3)
-
Nightly build (bleeding edge)
Environment
- Command line
- Python
- R
- Java
- Node.js
- Rust
- Go
- C/C++
- ODBC
Platform
- Windows
- macOS
- Linux
The package is available for all platforms.
Download method
- Package manager
- Direct download
Architecture
- x86_64
- arm64
The package supports both architectures.
Installation
Link
Usage example