Amazon Athena Connector for Python

Prerequisites

Before we begin, make sure you meet the following prerequisite: Java Runtime Environment (JRE) or Java Development Kit (JDK) must be installed on your system.

• Minimum required version: Java 8
  • Amazon Corretto 8
  • Oracle JRE 8
• Recommended Java version: Java 21
  • Amazon Corretto 21
  • Oracle JRE 21

If your JDBC Driver targets a different Java version (e.g., 11 / 17 / 21), install the corresponding or newer Java version.

Download Amazon Athena JDBC driver

To connect to Amazon Athena in , you will have to download JDBC driver for it, which we will use in later steps. Let's perform these little steps right away:

1. Visit Amazon Athena official website.
2. Download the JDBC driver, and save it locally, e.g. to D:\Drivers\JDBC\athena-jdbc.jar.
3. Done! That was easy, wasn't it? Let's proceed to the next step.

Create ODBC Data Source (DSN) based on ZappySys JDBC Bridge Driver

Step-by-step instructions

To get data from Amazon Athena using Python we first need to create a DSN (Data Source) which will access data from Amazon Athena. We will later be able to read data using Python. Perform these steps:

1. Download and install ODBC PowerPack.

2. Open ODBC Data Sources (x64):

   

3. Create a User data source (User DSN) based on ZappySys JDBC Bridge Driver:

   ZappySys JDBC Bridge Driver

   
   • Create and use User DSN if the client application is run under a User Account. This is an ideal option in design-time, when developing a solution, e.g. in Visual Studio 2019. Use it for both type of applications - 64-bit and 32-bit.
   • Create and use System DSN if the client application is launched under a System Account, e.g. as a Windows Service. Usually, this is an ideal option to use in a production environment. Use ODBC Data Source Administrator (32-bit), instead of 64-bit version, if Windows Service is a 32-bit application.

4. Now, we need to configure the JDBC connection in the new ODBC data source. Simply enter the Connection string, credentials, configure other settings, and then click Test Connection button to test the connection:

   AmazonAthenaDSN

   jdbc:athena://WorkGroup=primary;Region=us-east-1;Catalog=MyAwsDataCatalog;OutputLocation=s3://my-s3-bucket/;

   com.amazon.athena.jdbc.AthenaDriver

   D:\Drivers\JDBC\athena-jdbc.jar

   AKIAIOSFODNN7EXAMPLE

   ******************************

   []

   

   Use these values when setting parameters:

   • Connection string: jdbc:athena://WorkGroup=primary;Region=us-east-1;Catalog=MyAwsDataCatalog;OutputLocation=s3://my-s3-bucket/;
   • Driver class: com.amazon.athena.jdbc.AthenaDriver
   • JDBC driver file(s): D:\Drivers\JDBC\athena-jdbc.jar
   • User name: AKIAIOSFODNN7EXAMPLE
   • User password: ******************************
   • Connection parameters: []

5. You should see a message saying that connection test is successful:

   

   Otherwise, if you are getting an error, check out our Community for troubleshooting tips.

6. We are at the point where we can preview a SQL query. For more SQL query examples visit JDBC Bridge documentation:

   AmazonAthenaDSN

   SELECT * FROM "r53_rlogs"
   ORDER BY query_timestamp DESC

   

   SELECT * FROM "r53_rlogs"
   ORDER BY query_timestamp DESC

   You can also click on the <Select Table> dropdown and select a table from the list.

   The ZappySys JDBC Bridge Driver acts as a transparent intermediary, passing SQL queries directly to the JDBC driver, which then handles the query execution. This means the Bridge Driver simply relays the SQL query without altering it.

   Some JDBC drivers don't support INSERT/UPDATE/DELETE statements, so you may get an error saying "action is not supported" or a similar one. Please, be aware, this is not the limitation of ZappySys JDBC Bridge Driver, but is a limitation of the specific JDBC driver you are using.

7. Click OK to finish creating the data source.

Video Tutorial

Read data in Python

Using ODBC DSN

1. Use this code snippet to read the data using AmazonAthenaDSN data source:

   AmazonAthenaDSN')

   

2. When you run the code it will make the API call and read the data:

   

3. Here is Python program's code in text format:

   
       import pyodbc
       conn = pyodbc.connect('DSN=AmazonAthenaDSN')
   
       cursor = conn.cursor()
   
       #execute query to fetch data from API service
       cursor.execute("SELECT id,title FROM products")
   
       row = cursor.fetchone()
       while row:
           print(row)
           row = cursor.fetchone()
   
       ##For loop example
       #for row in cursor:
       #    print(row)
   

Using a full ODBC connection string

If you want to avoid being dependent on a DSN and creating multiple DSNs for each platform (x86, x64), then you can use a fully qualified connection string. Simply go to your DSN and copy the Connection String:

1. Open ODBC data source configuration and click Copy settings:
   

   ZappySys JDBC Bridge Driver - Configuration [Version: 2.0.1.10418]

   ZappySys JDBC Bridge Driver - Amazon Athena

   Amazon Athena Connector allows to connect to serverless, interactive analytics service that provides a simplified and flexible way to analyze petabytes of data where it lives.

   AmazonAthenaDSN

   
2. The window opens, telling us the connection string was successfully copied to the clipboard:

3. Then in your Python code use Connection String when initializing OdbcConnection object, for example:

   conn = pyodbc.connect('DRIVER={ZappySys JDBC Bridge Driver};ServiceUrl=https://yourservices.provider.com/api/xxxx....;AuthName=Http;')

How to install `pyodbc` in the Python?

Centralized data access via Data Gateway

In some situations, you may need to provide Amazon Athena data access to multiple users or services. Configuring the data source on a Data Gateway creates a single, centralized connection point for this purpose.

This configuration provides two primary advantages:

• Centralized data access
  The data source is configured once on the gateway, eliminating the need to set it up individually on each user's machine or application. This significantly simplifies the management process.
• Centralized access control
  Since all connections route through the gateway, access can be governed or revoked from a single location for all users.

If you need any of these requirements, you will have to create a data source in Data Gateway to connect to Amazon Athena, and to create an ODBC data source to connect to Data Gateway in Python.

Let's not wait and get going!

Creating Amazon Athena data source in Gateway

In this section we will create a data source for Amazon Athena in Data Gateway. Let's follow these steps to accomplish that:

1. Search for gateway in Windows Start Menu and open ZappySys Data Gateway Configuration:

   

2. Go to Users tab and follow these steps to add a Data Gateway user:

   • Click Add button
   • In Login field enter username, e.g., john
   • Then enter a Password
   • Check Is Administrator checkbox
   • Click OK to save
   

3. Now we are ready to add a data source:

   • Click Add button
   • Give Datasource a name (have it handy for later)
   • Then select Native - ZappySys JDBC Bridge Driver
   • Finally, click OK
   AmazonAthenaDSN

   ZappySys JDBC Bridge Driver

   

4. When the ZappySys JDBC Bridge Driver configuration window opens, configure the Data Source the same way you configured it in ODBC Data Sources (64-bit), in the beginning of this article.

5. Very important step. Now, after creating or modifying the data source make sure you:

   • Click the Save button to persist your changes.
   • Hit Yes, once asked if you want to restart the Data Gateway service.

   This will ensure all changes are properly applied:

   
   Skipping this step may result in the new settings not taking effect and, therefore you will not be able to connect to the data source.

Creating ODBC data source for Data Gateway

In this part we will create ODBC data source to connect to Data Gateway from Python. To achieve that, let's perform these steps:

1. Open ODBC Data Sources (x64):

   

2. Create a User data source (User DSN) based on ODBC Driver 17 for SQL Server:

   ODBC Driver 17 for SQL Server

   
   If you don't see ODBC Driver 17 for SQL Server driver in the list, choose a similar version driver.

3. Then set a Name of the data source (e.g. Gateway) and the address of the Data Gateway:

   GatewayDSN

   localhost,5000

   
   Make sure you separate the hostname and port with a comma, e.g. localhost,5000.

4. Proceed with authentication part:

   • Select SQL Server authentication
   • In Login ID field enter the user name you used in Data Gateway, e.g., john
   • Set Password to the one you configured in Data Gateway
   

5. Then set the default database property to AmazonAthenaDSN (the one we used in Data Gateway):

   AmazonAthenaDSN

   

6. Continue by checking Trust server certificate option:

   

7. Once you do that, test the connection:

   

8. If connection is successful, everything is good:

   

9. Done!

We are ready to move to the final step. Let's do it!

Accessing data in Python via Data Gateway

Finally, we are ready to read data from Amazon Athena in Python via Data Gateway. Follow these final steps:

1. Go back to Python.

2. Use this code snippet to read the data using GatewayDSN data source:

   GatewayDSN')

   

3. Read the data the same way we discussed at the beginning of this article.

4. That's it!

Now you can connect to Amazon Athena data in Python via the Data Gateway.

Troubleshooters & resources (JDBC Bridge Driver)

Below are some useful community articles to help you troubleshoot and configure the ZappySys JDBC Bridge Driver:

• How to combine multiple JAR files
  Learn how to merge multiple .jar dependencies when your JDBC driver requires more than one file.
• How to fix JBR error: “Data lake is not available / Unable to verify trust for server certificate chain”
  Resolve SSL or certificate validation issues encountered during JDBC connections.
• System Exception: “Java is not installed or not accessible”
  Fix Java path or environment issues that prevent the JDBC Bridge from launching Java.
• JDBC Bridge Driver disconnect from Java host error
  Troubleshoot unexpected disconnection problems between SSIS and the Java process.
• Error: Could not open jvm.cfg while using JDBC Bridge Driver
  Resolve JVM configuration path errors during driver initialization.
• How to enable JDBC Bridge Driver logging
  Enable detailed driver logging for better visibility during troubleshooting.
• How to pass JDBC connection parameters (not by URL)
  Learn how to specify connection properties programmatically instead of embedding them in the JDBC URL.
• How to fix JDBC Bridge error: “No connection could be made because the target machine actively refused it”
  Troubleshoot firewall or local port binding issues preventing communication with the Java host.
• How to use JDBC Bridge options (System Property for Java command line, e.g., classpath, proxy)
  Configure custom Java options like classpath and proxy using JDBC Bridge system properties.

Conclusion

In this article we showed you how to connect to Amazon Athena in Python and integrate data without any coding, saving you time and effort. It's worth noting that ZappySys JDBC Bridge Driver allows you to connect not only to Amazon Athena, but to any Java application that supports JDBC (just use a different JDBC driver and configure it appropriately).

We encourage you to download Amazon Athena Connector for Python and see how easy it is to use it for yourself or your team.

If you have any questions, feel free to contact ZappySys support team. You can also open a live chat immediately by clicking on the chat icon below.

Download Amazon Athena Connector for Python Documentation

More integrations

Other connectors for Python

Amazon Ads

Amazon Selling Partner (SP-API)

Apache Derby

Apache Hive

Apache Spark

Asana

Azure DevOps

Cosmos DB

Dropbox

ElasticSearch

FastSpring

Gmail

Google Ads

Google BigQuery

Google Calendar

Google Drive

Google Search Console

Google Sheets

Hubspot

Infor Data Lake

Jira

Mailchimp

ManagedEngine ServiceDesk Plus (Zoho)

MariaDB

OData

OneDrive

Outlook Mail (Office 365)

Parquet (DuckDB)

Power BI

ServiceNow

SharePoint Online

Shopify

Smartsheet

Starburst

Stripe

Trino

YouTube

Zendesk

Zoho CRM

Zoho SalesIQ

Zoom

REST API

JSON

JSON File

XML

SOAP

XML File

JDBC-ODBC Bridge

Salesforce

CSV

Amazon S3 JSON File

Amazon S3 XML File

Amazon S3 CSV File

Azure Blob JSON File

Azure Blob XML File

Azure Blob CSV File

FTP/SFTP JSON File

FTP/SFTP XML File

FTP/SFTP CSV File

Build your own Custom API Connector

Other application integration scenarios for Amazon Athena

SSIS

SQL Server

Power BI

SSRS

Informatica

MS Access

MS Excel

SSAS

C#

Tableau

SAP Crystal Reports

Azure Data Factory (Pipeline)

Azure Data Factory (SSIS)

Talend Studio

UiPath

PowerShell

ODBC