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Python

Amazon Athena Python Connector

SQL-based access to Amazon Athena from Python

Easily connect Python-based data access, visualization, ORM, ETL, AI/ML, and custom apps with Amazon Athena!

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Python Connector Libraries for Amazon Athena Data Connectivity. Integrate Amazon Athena with popular Python tools like Pandas, SQLAlchemy, Dash & petl. Easy-to-use Python Database API (DB-API) Modules connect Amazon Athena data with Python and any Python-based applications.

Features

Connect to live Amazon Athena data, for real-time data access with the Amazon Athena ODBC Driver
Full support for data aggregation and complex JOINs in SQL queries
Seamless integration with leading BI, reporting, and ETL tools and with custom applications via the Amazon Athena Connector.

Specifications

Python Database API (DB-API) Modules for Amazon Athena.
Write SQL, get Amazon Athena data. Access Amazon Athena through standard Python Database Connectivity.
Integration with popular Python tools like Pandas, SQLAlchemy, Dash & petl.
Integrate Python-based Apps with Amazon Athena interactive query services!
Full Unicode support for data, parameter, & metadata.

CData Python connectors in action!

Watch the video overview for a first hand-look at the powerful data integration capabilities included in the CData Python Connectors.

Watch the Python Connector Video Overview

Python connectivity with Amazon Athena

Full-featured and consistent SQL access to any supported data source through Python


Connecting to Amazon Athena with Python

CData Python Connectors leverage the Database API (DB-API) interface to make it easy to work with Amazon Athena from a wide range of standard Python data tools. Connecting to and working with your data in Python follows a basic pattern, regardless of data source:

  • Configure the connection properties to Amazon Athena
  • Query Amazon Athena to retrieve or update data
  • Connect your Amazon Athena data with Python data tools.


Connecting to Amazon Athena in Python

To connect to your data from Python, import the extension and create a connection:

Once you import the extension, you can work with all of your enterprise data using the python modules and toolkits that you already know and love, quickly building apps that help you drive business.

import cdata.amazonathena as mod
conn = mod.connect("[email protected]; Password=password;")

#Create cursor and iterate over results
cur = conn.cursor()
cur.execute("SELECT * FROM AthenaTables")
	
rs = cur.fetchall()
	
for row in rs:
print(row)
		
engine = create_engine("amazonathena///Password=password&User=user")

df = pandas.read_sql("SELECT * FROM AthenaTables", engine)

df.plot()
plt.show()

Visualize Amazon Athena Data with pandas

The data-centric interfaces of the Amazon Athena Python Connector make it easy to integrate with popular tools like pandas and SQLAlchemy to visualize data in real-time.

AI-assisted development with CData CLI

Build Amazon Athena integrations faster with AI that understands your schema

Schema-aware AI

CData CLI gives AI coding tools access to your Amazon Athena schema. No more guessing table names or column types—AI sees the same metadata in your Python Connectors.

Your AI Knows SQL

How to find table names, column names, and how to generate SQL syntax are things that AI knows well from millions of training data. No need for customization, no hallucinations. Your AI acts like a domain specialist to Amazon Athena.

More Accurate, More Token-Efficient

With CData CLI's queryable schema detection and highly efficient queries with filters, aggregation, joins with correct pushdown, your AI will achieve more accuracy with less token usage.

Supported AI Coding Tools
Download CData CLI