apache-airflow-providers-salesforce
Provider package apache-airflow-providers-salesforce for Apache Airflow
Decision gist · record as of 2026-08-14
Yes, if you run Apache Airflow and need to integrate Salesforce into your data workflows. The package is production-stable, actively maintained, has no known vulnerabilities, and carries a permissive license. Install friction is low. The only gotcha is the hard dependency on Airflow >=2.11.0 and valid Salesforce credentials—if you don't have an Airflow deployment already, this package alone won't help.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires an existing Apache Airflow >=2.11.0 installation and valid Salesforce API credentials configured in Airflow connections.
- Low friction installation as a pure-Python wheel.
- Active maintenance with a release 6 days old; the parent Apache Airflow project has strong community backing (46490 stars).
License · maintenance · safety
Apache-2.0 (permissive) — Apache License 2.0 (permissive). You may use, modify, and distribute this package freely in commercial and private projects, with minimal restrictions beyond attribution and liability disclaimers.
last release 2026-08-08 (6 days) · last repo commit 2026-08-14 · 46,490 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 969,934 downloads/mo, #4,610 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-salesforce
from airflow.providers.salesforce.operators.salesforce import SalesforceToS3Operator
# Use in a DAG to export Salesforce data- Specific operators and hooks available in this version beyond what the excerpt describes.
- Whether pandas version constraints (2.1.2+ for Python <3.13, 2.2.3+ for 3.13–3.14, 2.3.3+ for >=3.14) affect common workflows.
- Performance characteristics when handling large Salesforce datasets.
What it is and what it does
This is an Apache Airflow provider package that adds Salesforce connectivity to Airflow workflows. It wraps the simple-salesforce library and pandas to enable scheduled, programmatic access to Salesforce data—querying records, exporting to cloud storage, or loading data into Salesforce as part of larger data pipelines. The package is maintained as part of the Apache Airflow project and follows Airflow's provider architecture, meaning it integrates cleanly with Airflow's DAG execution model, connection management, and operator framework.
You install it alongside an existing Airflow deployment (minimum version 2.11.0) and then use its operators and hooks within your DAG definitions. It supports Python 3.10 through 3.14 and has no known security vulnerabilities. The package is actively maintained—the latest release is recent—and sits in the top 5000 PyPI packages by download volume, indicating real production use.
Use it for
- Export Salesforce records to S3 or another cloud store on a daily or hourly schedule.
- Load transformed data from a data lake back into Salesforce as a scheduled batch job.
- Monitor Salesforce data quality by running periodic queries and alerting on anomalies.
- Synchronize Salesforce records with an internal database as part of a multi-step ETL pipeline.
- Archive historical Salesforce data to cold storage on a retention schedule.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you run Apache Airflow and need to integrate Salesforce into your data workflows.
The package is production-stable, actively maintained, has no known vulnerabilities, and carries a permissive license. Install friction is low. The only gotcha is the hard dependency on Airflow >=2.11.0 and valid Salesforce credentials—if you don't have an Airflow deployment already, this package alone won't help.
Install
apache-airflow-providers-salesforce on PyPI
Before you install
Low friction installation as a pure-Python wheel. Active maintenance with a release 6 days old; the parent Apache Airflow project has strong community backing (46490 stars). Requires Apache Airflow >=2.11.0 and four runtime dependencies including simple-salesforce and pandas.
Requires an existing Apache Airflow >=2.11.0 installation and valid Salesforce API credentials configured in Airflow connections.
License in practice
Apache License 2.0 (permissive). You may use, modify, and distribute this package freely in commercial and private projects, with minimal restrictions beyond attribution and liability disclaimers.
Quickstart
pip install apache-airflow-providers-salesforce
from airflow.providers.salesforce.operators.salesforce import SalesforceToS3Operator
# Use in a DAG to export Salesforce dataVerify before relying
- Specific operators and hooks available in this version beyond what the excerpt describes.
- Whether pandas version constraints (2.1.2+ for Python <3.13, 2.2.3+ for 3.13–3.14, 2.3.3+ for >=3.14) affect common workflows.
- Performance characteristics when handling large Salesforce datasets.
Package facts
| License | Apache-2.0 permissive |
| Python support | Supports the current Python release >=3.10 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 4 packagesapache-airflowapache-airflow-providers-common-compatsimple-salesforcepandas |
| Maintenance | Actively maintained 6 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 969,934 / month, #4,610 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_salesforce-5.14.2-py3-none-any.whl
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See also apache-airflow-providers-alibaba · apache-airflow-providers-apache-hdfs · apache-airflow-providers-exasol · apache-airflow-providers-presto · apache-airflow-providers-weaviate · apache-airflow-providers-yandex · apache-airflow-providers-trino · apache-airflow-providers-papermill · apache-airflow-providers-neo4j · apache-airflow-providers-databricks