{"categories":[{"label":"Monitoring","url":"https://skillfed.io/packages/category/system-monitoring/4"}],"enrichment":{"capability":"Integrates Presto query execution into Apache Airflow workflows, enabling scheduled and triggered SQL queries against Presto clusters with result handling via pandas DataFrames.","skillfed_tags":["airflow-provider","data-orchestration","sql-integration"],"use_cases":["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."],"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.\n\nTypically 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\u20133.14) and is actively maintained by the Apache Airflow project.","worth_installing":"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."},"id":"apache-airflow-providers-presto","links":{"html":"https://skillfed.io/packages/apache-airflow-providers-presto","md":"https://skillfed.io/packages/apache-airflow-providers-presto.md","pypi":"https://pypi.org/project/apache-airflow-providers-presto/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-08","license_spdx":"Apache-2.0","license_treatment":"permissive","name":"apache-airflow-providers-presto","python_support":"supports_current","summary":"Provider package apache-airflow-providers-presto for Apache Airflow"},"popularity":{"monthly_downloads":240846,"position":8897,"tier":"top_15000"},"security":{"n_vulnerabilities":0},"version":"5.12.1"}