How to integrate Metabase with Amazon S3 Data

Metabase is an open source data visualization tool that allows users to create interactive dashboards. When paired with CData Connect AI, users can easily create visualizations and dashboards linked to live Amazon S3 data. This article describes how to connect to Amazon S3 and build a simple visualization using Amazon S3 data.

CData Connect provides a pure cloud-to-cloud interface for Amazon S3, allowing you to easily integrate with live Amazon S3 data in Metabase — without replicating the data. Connect looks exactly like a SQL Server database to Metabase and uses optimized data processing out of the box to push all supported SQL operations (filters, JOINs, etc) directly to Amazon S3, leveraging server-side processing to quickly return Amazon S3 data.

Configure Amazon S3 Connectivity for Metabase

Connectivity to Amazon S3 from Metabase is made possible through CData Connect AI. To work with Amazon S3 data from Metabase, we start by creating and configuring a Amazon S3 connection.

1. Log into Connect AI, click Sources, and then click Add Connection
👁 Adding a Connection

2. Select "Amazon S3" from the Add Connection panel
👁 Selecting a data source

3. Enter the necessary authentication properties to connect to Amazon S3.

   To authorize Amazon S3 requests, provide the credentials for an administrator account or for an IAM user with custom permissions. Set AccessKey to the access key Id. Set SecretKey to the secret access key.

   Note: You can connect as the AWS account administrator, but it is recommended to use IAM user credentials to access AWS services.

   For information on obtaining the credentials and other authentication methods, refer to the Getting Started section of the Help documentation.

   👁 Configuring a connection (Salesforce is shown)
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Amazon S3 Connection page and update the User-based permissions. 👁 Updating permissions
   

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create. 👁 Creating a new PAT
   
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to Amazon S3 data from Metabase.

Connect to CData Connect AI from Metabase

After creating the connection in Connect AI, navigate to your Metabase instance. Use the SQL Server interface to connect to Connect AI.

1. Navigate to the administration screen (Settings -> Admin) and click "Add Database" from the "Databases" tab 👁 Adding a new database connection to Metabase.
   
2. Configure the connection to Connect AI and click "Save"
   • Database type: Select "SQL Server"
   • Name: Name the connection (e.g. "Amazon S3 (Connect AI)")
   • Host: tds.cdata.com
   • Port: 14333
   • Database name: The name of the connection you just created (e.g. AmazonS31)
   • Username: A Connect AI username (e.g. [email protected])
   • Password: The PAT previously created
   • Click to Use a secure connection (SSL)
   👁 Configuring the connection to Connect AI.
   

Execute Amazon S3 Data with Metabase

Once you configure the connection to Connect AI, you can query Amazon S3 and build visualizations.

1. Use the "Write SQL" tool to retrieve the Amazon S3 data 👁 Click the 'Write SQL' button.
   
2. Write a SQL query based on the Amazon S3 connection in CData Connect AI, e.g.
   
   

   SELECT Name, OwnerId FROM ObjectsACL WHERE Name = 'TestBucket'

   👁 Collected data (Salesforce is shown).
   
3. Navigate to the "Visualization" screen, choose a visualization, and configure the visualization 👁 Collected data (Salesforce is shown).
   

More Information & Free Trial

At this point, you have built a simple visualization from Amazon S3 data in Metabase. You can continue to work with live Amazon S3 data in Metabase just like you would any SQL Server database. For more information on creating a live connection to Amazon S3 (and more than 100 other data sources), visit the Connect AI page. Sign up for a free trial and start working with live Amazon S3 data in Metabase today.