apache-airflow-providers-elasticsearch
Provider package apache-airflow-providers-elasticsearch for Apache Airflow
Decision gist · record as of 2026-08-14
Yes, if you run Airflow and need to integrate Elasticsearch into your workflows. The package is actively maintained, carries no known vulnerabilities, has low install friction, and is part of the official Apache Airflow provider ecosystem. Install only if you have an Airflow instance >=2.11.0 and an Elasticsearch cluster >=8.10 to connect to.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires an existing Airflow installation (>=2.11.0) and an Elasticsearch cluster (>=8.10,<10) to connect to.
- Low install friction with a pure-Python wheel.
- Actively maintained—released 6 days ago with a large upstream repository (46490 stars).
License · maintenance · safety
Apache-2.0 (permissive) — Apache-2.0 permissive license allows commercial and private use with minimal restrictions; typical for Apache Foundation projects.
last release 2026-08-08 (6 days) · last repo commit 2026-08-14 · 46,490 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 712,443 downloads/mo, #5,254 on PyPI
Alternatives
Verify before relying
pip install apache-airflow-providers-elasticsearch
from airflow.providers.elasticsearch.hooks.elasticsearch import ElasticsearchHook
hook = ElasticsearchHook(conn_id='elasticsearch_default')
results = hook.search(index='my_index', query={'match_all': {}})- Specific operators and sensors available beyond hooks (e.g., ElasticsearchOperator, ElasticsearchSensor).
- Whether polars optional dependency adds data transformation capabilities or is only for export/import workflows.
What it is and what it does
This is an Apache Airflow provider package that bridges Airflow workflows and Elasticsearch clusters. It supplies hooks, operators, and sensors that let you query Elasticsearch indices, index documents, and monitor cluster health as part of your Airflow DAGs. The package is built on top of the official elasticsearch client library and integrates with Airflow's connection and credential management system.
You install it alongside an existing Airflow deployment (>=2.11.0) to gain Elasticsearch-aware task types. It depends on apache-airflow, elasticsearch (8.10 or later, before 10.0), and two common Airflow provider packages for compatibility and SQL-like operations. The package supports Python 3.10 through 3.14 and includes an optional polars dependency for advanced data handling.
Use it for
- Index log or event data into Elasticsearch from Airflow tasks as part of a data pipeline.
- Query Elasticsearch indices to fetch metrics or alerts and trigger downstream DAG logic based on results.
- Monitor Elasticsearch cluster health or index status and raise alerts via Airflow sensors.
- Build ETL workflows that read from Elasticsearch, transform data, and write back or to other systems.
- Orchestrate bulk indexing or reindexing operations across Elasticsearch clusters on a schedule.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you run Airflow and need to integrate Elasticsearch into your workflows.
The package is actively maintained, carries no known vulnerabilities, has low install friction, and is part of the official Apache Airflow provider ecosystem. Install only if you have an Airflow instance >=2.11.0 and an Elasticsearch cluster >=8.10 to connect to.
Install
apache-airflow-providers-elasticsearch on PyPI
Before you install
Low install friction with a pure-Python wheel. Actively maintained—released 6 days ago with a large upstream repository (46490 stars). Requires Airflow >=2.11.0 and elasticsearch >=8.10,<10.
Requires an existing Airflow installation (>=2.11.0) and an Elasticsearch cluster (>=8.10,<10) to connect to.
License in practice
Apache-2.0 permissive license allows commercial and private use with minimal restrictions; typical for Apache Foundation projects.
Quickstart
pip install apache-airflow-providers-elasticsearch
from airflow.providers.elasticsearch.hooks.elasticsearch import ElasticsearchHook
hook = ElasticsearchHook(conn_id='elasticsearch_default')
results = hook.search(index='my_index', query={'match_all': {}})Verify before relying
- Specific operators and sensors available beyond hooks (e.g., ElasticsearchOperator, ElasticsearchSensor).
- Whether polars optional dependency adds data transformation capabilities or is only for export/import workflows.
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-compatapache-airflow-providers-common-sqlelasticsearch |
| Maintenance | Actively maintained 6 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 712,443 / month, #5,254 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_elasticsearch-6.9.0-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 elasticsearch integration”
- apache-airflow-providers-elasticsearchIntegrates Elasticsearch with Apache Airflow, providing operators,…
- langchain-elasticsearchIntegrates Elasticsearch with LangChain to provide vector storage,…
- CMRESHandlerProvides a Python logging handler that sends log records directly to…
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-anomalo · apache-airflow-providers-opensearch · apache-airflow-providers-standard · apache-airflow-providers-arangodb · apache-airflow-providers-oracle · apache-airflow-providers-apache-pinot · apache-airflow-providers-zendesk · apache-airflow-providers-informatica · apache-airflow-providers-apache-cassandra · airflow-provider-hightouch