DuckDB: встраиваемая аналитика для CSV и Parquet без сервера
DuckDB — встраиваемая аналитическая СУБД для быстрой обработки CSV/Parquet без сервера, с SQL и интеграциями.
DuckDB — встраиваемая аналитическая СУБД для быстрой обработки CSV/Parquet без сервера, с SQL и интеграциями.
DuckDB можно использовать для обработки и анализа данных, которые генерируют AI-агенты: логи, метрики, результаты. Он позволяет быстро выполнять SQL-запросы к CSV/Parquet без настройки БД, что ускоряет разработку и отладку оркестрации.
расшифровка ролика ↓
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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/current/sql/dialect/friendly_sql.html).
DuckDB is available as a [standalone CLI application](https://duckdb.org/docs/current/clients/cli/overview) and has clients for [Python](https://duckdb.org/docs/current/clients/python/overview), [R](https://duckdb.org/docs/current/clients/r), [Java](https://duckdb.org/docs/current/clients/java), [Wasm](https://duckdb.org/docs/current/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/current/clients/r#duckplyr-dplyr-api).
For more information on using DuckDB, please refer to the [DuckDB documentation](https://duckdb.org/docs/current/).
## 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/current/data/overview) section for more information.
## SQL Reference
The documentation contains a [SQL introduction and reference](https://duckdb.org/docs/current/sql/introduction).
## Development
For development, DuckDB requires [CMake](https://cmake.org), Python 3 and a `C++17` 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/current/dev/building/overview) and [Contribution Guide](CONTRIBUTING.md).
## Support
See the [Support Options](https://ducklabs.com/support/) page and the dedicated [`endoflife.date`](https://endoflife.date/duckdb) page.