apache-airflow-providers-presto
Provider package apache-airflow-providers-presto for Apache Airflow
Decision gist · record as of 2026-08-14
Yes. This package is actively maintained, has no known vulnerabilities, installs with low friction, and is the standard way to run Presto queries in Airflow. Install it if you are already running Airflow and need to orchestrate Presto workloads; it is production-ready and widely used.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires an existing Apache Airflow installation (>=2.11.0) and a configured Presto connection in Airflow's connection backend.
- Low friction install as a pure Python wheel.
- Actively maintained with a release 6 days old.
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows use in commercial and proprietary projects with minimal restrictions; you must retain license notices and provide a copy of the license.
last release 2026-08-08 (6 days) · last repo commit 2026-08-14 · 46,490 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 240,846 downloads/mo, #8,897 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-presto
from airflow.providers.presto.operators.presto import PrestoOperator
task = PrestoOperator(
task_id='query_presto',
sql='SELECT * FROM my_table',
presto_conn_id='presto_default'
)- Whether the package includes hooks, sensors, or transfer operators beyond the base PrestoOperator.
- Support for Presto-specific features such as partitioned query execution or result caching.
- Whether optional sqlalchemy extra enables ORM-style query building.
What it is and what it does
This is an Apache Airflow provider package that adds Presto database connectivity to Airflow DAGs. It wraps the presto-python-client library and integrates with Airflow's task execution model, allowing you to define SQL queries as Airflow operators that run on a schedule or in response to upstream task completion. The package depends on apache-airflow, apache-airflow-providers-common-sql for shared SQL abstractions, pandas for result handling, and psycopg2-binary for PostgreSQL compatibility in certain configurations.
Typically used in data pipeline orchestration where you need to execute analytical or ETL queries against a Presto cluster as part of a larger workflow. The provider handles connection management, query execution, and result retrieval, abstracting away direct client library calls. It supports modern Python versions (3.10–3.14) and is actively maintained by the Apache Airflow project.
Use it for
- Schedule daily or hourly SQL aggregations on a Presto cluster as part of a data warehouse refresh pipeline.
- Trigger Presto queries conditionally based on upstream task results in a multi-step ETL workflow.
- Extract query results into pandas DataFrames for downstream Python processing or file export.
- Monitor Presto query execution and retry failed queries using Airflow's built-in retry and alerting mechanisms.
- Integrate Presto queries with Google Cloud Storage or other cloud providers via optional cross-provider dependencies.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes.
This package is actively maintained, has no known vulnerabilities, installs with low friction, and is the standard way to run Presto queries in Airflow. Install it if you are already running Airflow and need to orchestrate Presto workloads; it is production-ready and widely used.
Install
apache-airflow-providers-presto on PyPI
Before you install
Low friction install as a pure Python wheel. Actively maintained with a release 6 days old. Requires Apache Airflow 2.11.0 or later and modern Python (3.10–3.14); all runtime dependencies are stable, widely-used packages.
Requires an existing Apache Airflow installation (>=2.11.0) and a configured Presto connection in Airflow's connection backend.
License in practice
Apache-2.0 permissive license allows use in commercial and proprietary projects with minimal restrictions; you must retain license notices and provide a copy of the license.
Quickstart
pip install apache-airflow-providers-presto
from airflow.providers.presto.operators.presto import PrestoOperator
task = PrestoOperator(
task_id='query_presto',
sql='SELECT * FROM my_table',
presto_conn_id='presto_default'
)Verify before relying
- Whether the package includes hooks, sensors, or transfer operators beyond the base PrestoOperator.
- Support for Presto-specific features such as partitioned query execution or result caching.
- Whether optional sqlalchemy extra enables ORM-style query building.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 6 packagesapache-airflowapache-airflow-providers-common-compatapache-airflow-providers-common-sqlpresto-python-clientpandaspsycopg2-binary |
| Maintenance | Actively maintained 6 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 240,846 / month, #8,897 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableEnvironment :: ConsoleEnvironment :: Web EnvironmentFramework :: Apache AirflowFramework :: Apache Airflow :: ProviderIntended Audience :: DevelopersIntended Audience :: System AdministratorsProgramming Language :: Python :: 3.10Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: System :: Monitoring |
Evidence: apache_airflow_providers_presto-5.12.1-py3-none-any.whl
Tags
Let your AI agent find packages like this
Example. Real query, live index.
You found this page by searching. An agent finds it by wishing: SkillFed indexes 14,416 PyPI packages by what they can do, searchable in plain language.
wish › “airflow presto integration”
- apache-airflow-providers-prestoIntegrates Presto query execution into Apache Airflow workflows,…
- apache-airflow-providers-apache-hiveIntegrates Apache Hive with Apache Airflow, enabling Hive query…
- presto-python-clientProvides a Python DBAPI-compatible client to query Presto, a…
Give your agent the search over MCP, or paste the wish link into any chat.
More Monitoring packages
Wraps any iterable to display a real-time progress bar in the terminal or Jupyter notebook, showing iteration count, elapsed time, and estimated time remaining.
Provides generated Python code for OpenTelemetry semantic conventions, enabling standardized attribute naming and constant definitions for instrumentation and telemetry collection.
Install it if you are using OpenTelemetry and want to follow semantic conventions correctly.
Provides the reference implementation of the OpenTelemetry API for collecting and exporting traces, metrics, and logs from Python applications.
Provides the abstract API and interfaces for OpenTelemetry instrumentation in Python, defining how to emit traces, metrics, and logs without tying code to a specific SDK implementation.
Exports OpenTelemetry observability data to an OpenTelemetry Collector using Protobuf-encoded messages over HTTP.
Install it if you are using OpenTelemetry in Python and need to send data to a Collector over HTTP.
Provides automatic instrumentation commands and programmatic APIs to inject distributed tracing into Python applications without code changes, detecting and instrumenting packages used by your program.
Install it if you need distributed tracing without code changes and have compatible instrumented packages in your environment.
See also apache-airflow-providers-salesforce · apache-airflow-providers-trino · presto-python-client · apache-airflow-providers-databricks · apache-airflow-providers-mysql · apache-airflow-providers-exasol · apache-airflow-providers-postgres · apache-airflow-providers-apache-hive · apache-airflow-providers-common-sql · presto-types-parser