adbc-driver-quack 0.1.0a2

An Apache Arrow ADBC driver for DuckDB's Quack remote protocol.

adbc-driver-quack

An Apache Arrow ADBC driver for DuckDB's Quack remote protocol.

Returns Apache Arrow RecordBatches directly from a remote DuckDB server speaking Quack. Supports the standard ADBC bulk-ingest path (Statement.BindStream → APPEND_REQUEST) for fast column-oriented loads.

Distributed as:

• a Go module — github.com/gizmodata/adbc-driver-quack
• a pip install adbc-driver-quack wheel for Python (macOS / Linux / Windows × x64 / arm64)

Status: Alpha — v0.1.0-alpha.1 is the first release. The companion gizmodata/quack-jdbc JDBC driver is the same protocol from the JVM and is at v0.1.0-alpha.1 on Maven Central.

Quickstart

1. Start a Quack server (any DuckDB v1.5.2+)

-- in any DuckDB session, with the unsigned extensions flag enabled (`duckdb -unsigned`)
INSTALL quack FROM core_nightly;
LOAD quack;
CALL quack_serve('quack:127.0.0.1:9494', token=>'my-secret-token');

The server stays running until the DuckDB session exits. Press Ctrl-C in the DuckDB REPL to stop it.

2. Install the driver

Python:

pip install adbc-driver-quack

Go:

go get github.com/gizmodata/adbc-driver-quack@v0.1.0-alpha.1

3. Connect and query

import adbc_driver_quack.dbapi as quack
import pyarrow

with quack.connect(
    uri="quack://127.0.0.1:9494",
    db_kwargs={"adbc.quack.token": "my-secret-token"},
) as conn, conn.cursor() as cur:
    cur.execute("SELECT 42 AS answer, 'hello duckdb' AS greeting")
    table: pyarrow.Table = cur.fetch_arrow_table()
    print(table)

The result is a real pyarrow.Table — pass it straight to Polars, Pandas, DuckDB-in-process, ibis, or anything else that consumes Arrow:

import polars as pl
df = pl.from_arrow(table)

Alternative: drive adbc_driver_manager directly

If you prefer the adbc-quickstarts idiom — passing the driver to adbc_driver_manager.dbapi.connect rather than going through our wrapper — point at the bundled shared library via _driver_path():

from adbc_driver_manager import dbapi
import adbc_driver_quack

with dbapi.connect(
    driver=adbc_driver_quack._driver_path(),
    entrypoint="QuackDriverInit",
    db_kwargs={
        "uri": "quack://127.0.0.1:9494",
        "adbc.quack.token": "my-secret-token",
    },
) as conn, conn.cursor() as cur:
    cur.execute("SELECT 42 AS answer")
    table = cur.fetch_arrow_table()

Both styles work the same on the wire — pick whichever reads better for your codebase.

Streaming large result sets

Cursor.fetch_record_batch() returns a pyarrow.RecordBatchReader that pulls one server-side DataChunk per read_next_batch() call. Memory stays bounded by the server's chunk size (~2k rows) even when the result is millions of rows:

with conn.cursor() as cur:
    cur.execute("SELECT * FROM lineitem")  # arbitrary size
    reader = cur.fetch_record_batch()
    for batch in reader:
        process(batch)  # one ~2k-row Arrow batch at a time

Bulk ingest (Arrow → DuckDB)

import pyarrow as pa
import adbc_driver_quack.dbapi as quack

table = pa.table({"id": [1, 2, 3], "name": ["alice", "bob", "carol"]})
with quack.connect(uri="quack://127.0.0.1:9494", db_kwargs={"adbc.quack.token": "..."}) as conn, conn.cursor() as cur:
    cur.adbc_ingest(table_name="customers", data=table, mode="append")  # one APPEND_REQUEST per RecordBatch

Transactions (autocommit off)

import adbc_driver_quack.dbapi as quack

with quack.connect(
    uri="quack://127.0.0.1:9494",
    db_kwargs={"adbc.quack.token": "..."},
    autocommit=False,
) as conn, conn.cursor() as cur:
    cur.execute("INSERT INTO orders VALUES (1, 'pending')")
    cur.execute("INSERT INTO order_items VALUES (1, 'widget', 2)")
    conn.commit()  # both inserts persist atomically

Connection URL

quack://host[:port]

Option	Default	Notes
adbc.uri	—	Required. Pass as the uri= kwarg to quack.connect.
adbc.quack.token	(none)	Authentication token. Server-side token=> argument to quack_serve().
adbc.quack.tls	false	true → use https:// for the underlying HTTP transport.

The URI is its own kwarg; everything else goes through db_kwargs:

import adbc_driver_quack.dbapi as quack

quack.connect(
    uri="quack://127.0.0.1:9494",
    db_kwargs={
        "adbc.quack.token": "my-secret-token",
        "adbc.quack.tls": "false",
    },
)

Why ADBC and not JDBC?

Both drivers speak the same protocol to the same kind of server. Pick the one that fits your runtime:

You're using	Reach for
A JVM tool (DBeaver, IntelliJ, Spark, dbt-jdbc, plain java.sql)	quack-jdbc
Python (pip install), Go, Rust, R, anything via ADBC C ABI	this driver
You want zero-copy Arrow data end-to-end	this driver

Repo layout

adbc-driver-quack/
├── go.mod, go.sum
├── internal/
│   ├── codec/       — BinaryReader/Writer for DuckDB BinarySerializer
│   ├── quacktype/   — Logical / physical / extra type system + codec
│   ├── message/     — DataChunk, DecodedVector, MessageCodec, VectorCodec
│   └── transport/   — QuackURI parser + net/http transport (IPv4/IPv6 fallback)
├── driver/quack/    — pure-Go ADBC Driver/Database/Connection/Statement impl
├── pkg/quack/       — cgo c-shared wrapper (produces libadbc_driver_quack.{so,dylib,dll})
├── python/          — Python wheel sources (adbc_driver_quack)
└── .github/         — CI: go test, python tests, cibuildwheel matrix, PyPI publish

The internal/ layer is a clean-room Go port of the matching Java packages in quack-jdbc.

Credits

• Wire format: DuckDB Quack protocol
• Codec design: ported from gizmodata/quack-jdbc (MIT), which itself was clean-room ported from tobilg/quack-protocol (MIT)
• ADBC framework: Apache Arrow ADBC (Apache-2.0)

License

MIT — see LICENSE for full attribution.