# duckdb

**Repository Path**: mirrors/duckdb

## Basic Information

- **Project Name**: duckdb
- **Description**: DuckDB，是一个可嵌入的 SQL OLAP 数据库管理系统
- **Primary Language**: Unknown
- **License**: MIT
- **Default Branch**: main
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 16
- **Forks**: 9
- **Created**: 2019-07-01
- **Last Updated**: 2025-08-16

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

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## DuckDB

DuckDB is a high-performance analytical database system. It is designed to be fast, reliable, portable, and easy to use. DuckDB provides a rich SQL dialect with support far beyond basic SQL. DuckDB supports arbitrary and nested correlated subqueries, window functions, collations, complex types (arrays, structs, maps), and [several extensions designed to make SQL easier to use](https://duckdb.org/docs/stable/sql/dialect/friendly_sql.html).

DuckDB is available as a [standalone CLI application](https://duckdb.org/docs/stable/clients/cli/overview) and has clients for [Python](https://duckdb.org/docs/stable/clients/python/overview), [R](https://duckdb.org/docs/stable/clients/r), [Java](https://duckdb.org/docs/stable/clients/java), [Wasm](https://duckdb.org/docs/stable/clients/wasm/overview), etc., with deep integrations with packages such as [pandas](https://duckdb.org/docs/guides/python/sql_on_pandas) and [dplyr](https://duckdb.org/docs/stable/clients/r#duckplyr-dplyr-api).

For more information on using DuckDB, please refer to the [DuckDB documentation](https://duckdb.org/docs/stable/).

## Installation

If you want to install DuckDB, please see [our installation page](https://duckdb.org/docs/installation/) for instructions.

## Data Import

For CSV files and Parquet files, data import is as simple as referencing the file in the FROM clause:

```sql
SELECT * FROM 'myfile.csv';
SELECT * FROM 'myfile.parquet';
```

Refer to our [Data Import](https://duckdb.org/docs/stable/data/overview) section for more information.

## SQL Reference

The documentation contains a [SQL introduction and reference](https://duckdb.org/docs/stable/sql/introduction).

## Development

For development, DuckDB requires [CMake](https://cmake.org), Python 3 and a `C++11` compliant compiler. In the root directory, run `make` to compile the sources. For development, use `make debug` to build a non-optimized debug version. You should run `make unit` and `make allunit` to verify that your version works properly after making changes. To test performance, you can run `BUILD_BENCHMARK=1 BUILD_TPCH=1 make` and then perform several standard benchmarks from the root directory by executing `./build/release/benchmark/benchmark_runner`. The details of benchmarks are in our [Benchmark Guide](benchmark/README.md).

Please also refer to our [Build Guide](https://duckdb.org/docs/stable/dev/building/overview) and [Contribution Guide](CONTRIBUTING.md).

## Support

See the [Support Options](https://duckdblabs.com/support/) page.