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duckdb-rs

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duckdb-rs is an ergonomic wrapper for using duckdb from Rust. It attempts to expose an interface similar to rusqlite. Actually the initial code and even this README is forked from rusqlite as duckdb also tries to expose a sqlite3 compatible API.

use duckdb::{params, Connection, Result};

// In your project, we need to keep the arrow version same as the version used in duckdb.
// Refer to https://github.com/duckdb/duckdb-rs/issues/92
// You can either:
use duckdb::arrow::record_batch::RecordBatch;
// Or in your Cargo.toml, use * as the version; features can be toggled according to your needs
// arrow = { version = "*", default-features = false, features = ["prettyprint"] }
// Then you can:
// use arrow::record_batch::RecordBatch;

use duckdb::arrow::util::pretty::print_batches;

#[derive(Debug)]
struct Person {
    id: i32,
    name: String,
    data: Option<Vec<u8>>,
}

fn main() -> Result<()> {
    let conn = Connection::open_in_memory()?;

    conn.execute_batch(
        r"CREATE SEQUENCE seq;
          CREATE TABLE person (
                  id              INTEGER PRIMARY KEY DEFAULT NEXTVAL('seq'),
                  name            TEXT NOT NULL,
                  data            BLOB
                  );
        ")?;

    let me = Person {
        id: 0,
        name: "Steven".to_string(),
        data: None,
    };
    conn.execute(
        "INSERT INTO person (name, data) VALUES (?, ?)",
        params![me.name, me.data],
    )?;

    // query table by rows
    let mut stmt = conn.prepare("SELECT id, name, data FROM person")?;
    let person_iter = stmt.query_map([], |row| {
        Ok(Person {
            id: row.get(0)?,
            name: row.get(1)?,
            data: row.get(2)?,
        })
    })?;

    for person in person_iter {
        let p = person.unwrap();
        println!("ID: {}", p.id);
        println!("Found person {:?}", p);
    }

    // query table by arrow
    let rbs: Vec<RecordBatch> = stmt.query_arrow([])?.collect();
    print_batches(&rbs).unwrap();
    Ok(())
}

Examples

The following examples demonstrate various features and use cases of duckdb-rs:

  • basic - Basic usage including creating tables, inserting data, and querying with and without Arrow.
  • appender - Bulk data insertion using the appender API with transactions.
  • parquet - Reading Parquet files directly using DuckDB's Parquet extension.
  • repl - Interactive SQL REPL.
  • hello-ext - A loadable DuckDB extension using the legacy extension API.
  • hello-ext-capi - A loadable DuckDB extension using the modern extension API.

Run any example with cargo run --example <name>.

Feature flags

The duckdb crate provides a number of Cargo features that can be enabled to add functionality:

Virtual tables and functions

  • vtab - Base support for creating custom table functions and virtual tables.
  • vtab-arrow - Apache Arrow integration for virtual tables. Enables conversion between Arrow RecordBatch and DuckDB data chunks.
  • vtab-excel - Read Excel (.xlsx) files directly in SQL queries with automatic schema detection.
  • vtab-loadable - Support for creating loadable DuckDB extensions. Includes procedural macros for extension development.
  • vscalar - Create custom scalar functions that operate on individual values or rows.
  • vscalar-arrow - Arrow-optimized scalar functions for vectorized operations.

Data integration

  • json - Enables reading and writing JSON files. Requires bundled.
  • parquet - Enables reading and writing Parquet files. Requires bundled.
  • appender-arrow - Efficient bulk insertion of Arrow data into DuckDB tables.
  • polars - Integration with Polars DataFrames.

Convenience features

  • vtab-full - Enables all virtual table features: vtab-excel, vtab-arrow, and appender-arrow.
  • extensions-full - Enables all major extensions: json, parquet, and vtab-full.
  • modern-full - Enables modern Rust ecosystem integrations: chrono, serde_json, url, r2d2, uuid, and polars.

Build configuration

  • bundled - Uses a bundled version of DuckDB's source code and compiles it during build. This is the simplest way to get started and avoids needing DuckDB system libraries.
  • buildtime_bindgen - Use bindgen at build time to generate fresh bindings instead of using pre-generated ones.
  • loadable-extension - Experimental support for building extensions that can be dynamically loaded into DuckDB.

Notes on building duckdb and libduckdb-sys

libduckdb-sys is a separate crate from duckdb-rs that provides the Rust declarations for DuckDB's C API. By default, libduckdb-sys attempts to find a DuckDB library that already exists on your system using pkg-config, or a Vcpkg installation for MSVC ABI builds.

You can adjust this behavior in a number of ways:

  • If you use the bundled feature, libduckdb-sys will use the cc crate to compile DuckDB from source and link against that. This source is embedded in the libduckdb-sys crate and as we are still in development, we will update it regularly. After we are more stable, we will use the stable released version from duckdb. This is probably the simplest solution to any build problems. You can enable this by adding the following in your Cargo.toml file:

    cargo add duckdb --features bundled

    Cargo.toml will be updated.

    [dependencies]
    # Assume that version DuckDB version 0.9.2 is used.
    duckdb = { version = "0.9.2", features = ["bundled"] }
  • When linking against a DuckDB library already on the system (so not using any of the bundled features), you can set the DUCKDB_LIB_DIR environment variable to point to a directory containing the library. You can also set the DUCKDB_INCLUDE_DIR variable to point to the directory containing duckdb.h.
  • Installing the duckdb development packages will usually be all that is required, but the build helpers for pkg-config and vcpkg have some additional configuration options. The default when using vcpkg is to dynamically link, which must be enabled by setting VCPKGRS_DYNAMIC=1 environment variable before build.

Binding generation

We use bindgen to generate the Rust declarations from DuckDB's C header file. bindgen recommends running this as part of the build process of libraries that used this. We tried this briefly (duckdb 0.10.0, specifically), but it had some annoyances:

  • The build time for libduckdb-sys (and therefore duckdb) increased dramatically.
  • Running bindgen requires a relatively-recent version of Clang, which many systems do not have installed by default.
  • Running bindgen also requires the DuckDB header file to be present.

So we try to avoid running bindgen at build-time by shipping pregenerated bindings for DuckDB.

If you use the bundled features, you will get pregenerated bindings for the bundled version of DuckDB. If you want to run bindgen at buildtime to produce your own bindings, use the buildtime_bindgen Cargo feature.

Contributing

See to Contributing.md

Checklist

  • Run cargo +nightly fmt to ensure your Rust code is correctly formatted.
  • Run cargo clippy --fix --allow-dirty --all-targets --workspace --all-features -- -D warnings to fix all clippy issues.
  • Ensure cargo test --all-targets --workspace --features "modern-full extensions-full" reports no failures.

TODOs

  • Refactor the ErrorCode part, it's borrowed from rusqlite, we should have our own
  • Support more type
  • Update duckdb.h
  • Adjust the code examples and documentation
  • Delete unused code / functions
  • Add CI
  • Publish to crate

License

DuckDB and libduckdb-sys are available under the MIT license. See the LICENSE file for more info.