Connector SDK Beta

Fivetran’s Connector SDK allows you to code a custom data connector using Python and deploy it as an extension of Fivetran. Fivetran automatically manages running Connector SDK connections on your scheduled frequency and manages the required compute resources.

Set up your data pipeline

Quickstart Guide

Quick refresher for those already familiar with the Connector SDK.

Detailed Guide

Learn about advanced examples of Connector SDK and how to create and configure the environment for Connector SDK.

Methods and Operations used by Connector SDK

Learn about the required object, methods and operations used by Connector SDK.

The Connector SDK service is the best fit for the following use cases:

• Fivetran doesn't have a connector for your source or is unlikely to support it in the near future.
• You are using private APIs, custom applications, unsupported file formats or those that require pre-processing.
• You have sensitive data that needs filtering or anonymizing before entering the destination.
• You don't want to introduce a 3rd party in to your pipeline eg to host a custom function

Features

Our Connector SDK enables you to create connectors with many of the same intrinsic capabilities as our standard Fivetran connectors, including:

• Column blocking
• Column hashing
• Source data type inference
• Automatic schema updates
• Data de-deduplication
• Destination ingestion optimizations

It also enables you to implement other features typically seen in Fivetran connectors if the source allows:

• Incremental updates
• Soft delete
• Table-level re-sync

When building a data pipeline using the Connector SDK, given that all prerequisites are in place, the high-level end state workflow is as follows:

1. You write code to extract data from your source and pass to the Fivetran Connector SDK.
2. Test and deploy your code to Fivetran, which creates your connection.
3. When running a sync, Fivetran runs your custom code so that it can extract data from your source and send it to Fivetran.
4. Fivetran then loads the data into your destination.

Resources

Visit the Connector SDK Github Repo and see our Connector SDK Detailed Guide to explore our Connector SDK.

Architecture

The following diagram shows a high-level overview of how connectors built using the Fivetran Connector SDK work:

The Connector SDK runtime environment executes your submitted Python script in an isolated environment. It installs the libraries listed in the requirements.txt file, and after installation, it runs the provided Python script and we pre-install the msodbcsql17 and msodbcsql18 drivers for connecting to Microsoft SQL server. We also pre-install libpq5 and libpq-dev, which is required to support psycopg and psycopg2, respectively.

By default, we host and run your Connector SDK connection in GCP, Fivetran's default infrastructure provider, in the region that you have configured in your destination. If you are on our Enterprise or Business Critical plan, you have the option to choose a cloud service provider and cloud region. In that case, we will host and run your code in the cloud provider and region you selected for the rest of your Fivetran infrastructure.

Secrets management

Configuration values are stored securely and encrypted in the same way as other Fivetran connectors' credentials. See our Data Credential Encryption documentation for more details. To pass configuration values to Fivetran for use in your code, you must upload them using the configuration.json file. Fivetran does not store this file and we suggest that you delete it from your project after deploying a Connector SDK project. Fivetran reads the values, encrypts them, and stores them securely. The values are only available to your code at runtime. You can confidently use configuration.json to pass any credentials required to run your connection, like a key required to make an API call.

System resources

The environment running your code has:

• 1 GB of RAM
• Less than 0.5 vCPUs of an 8 Core N2 or equivalent machine

Our production infrastructure allows for some variation in resources available to your connections at any given moment, load balancing across multiple connections.

What are the benefits of using Connector SDK?

• The Connector SDK supports many Fivetran features natively.
• You can leverage Fivetran's under-the-hood technology.
• You can test locally before deploying to Fivetran.
• The Connector SDK removes timeout and data size limitations seen in AWS Lambda.
• The Connector SDK code you write is hosted by Fivetran, no dealing with a third party.

Which Fivetran plans allow the use of Connector SDK?

The Connector SDK is available to all Fivetran customers.

What’s the difference between Connector SDK, Functions, and Lite connectors?

Lite connectors are API-based connectors that Fivetran builds by request. They are generally for SaaS APIs that produce a non-dynamic schema.

In contrast, you or your engineering team build connectors using a cloud function service or the Connector SDK and then deploy them to run either on the cloud service infrastructure or on top of the Fivetran platform.

The following table summarizes the key differences between connectors built via our By Request program, using a Cloud Function, and using Connector SDK:

What’s the difference between connectors built using Connector SDK and Partner-Built connectors?

Partner-Built connectors are built by Fivetran partners using our Partner SDK and are available for all Fivetran customers. The Partner SDK supports the following types of connectors:

• Source connectors
• Destination connectors

You build custom connectors using the Connector SDK, which are only available for you to use. Our Connector SDK only supports building source connectors.

What features does the Connector SDK support?

The Connector SDK supports many Fivetran features natively as if the connector was created by Fivetran, including:

• Any connection method supported by Python libraries that you can include in your Python requirement.txt file
• Updating and upserting data operations and soft deletion of data if source allows
• Customizing the data schema delivered to your destination
• Defining data types in the schema used to deliver data to your destination
• Control the state and connector-level re-syncs of the connection
• Authentication using OAuth 2.0 Client Credentials flow

The Connector SDK doesn't support the following features:

• Providing webhooks to receive event data
• History Mode
• Table-level re-syncs from the Fivetran dashboard
• Hybrid Deployment
• Powered by Fivetran

You can implement the following features in your custom code, if the source allows:

• Incremental data sync
• Soft deletion of data
• Table-level re-sync
• Multi-threading for fast extraction of data from the source

Can I use a hosted Python Environment like Jupyter Notebooks for this?

You can absolutely use a hosted environment to test out Python libraries and approaches to validate how you are going to connect to your data source and manipulate the response data ready for sending to Fivetran.

However, the actual connector.py file that you write will be sent to Fivetran and executed in our infrastructure each time a sync is triggered. As such, it needs to be a standalone Python script or a set of scripts that are called from your connector.py file.

How is pricing calculated for Connector SDK?

Connector SDK uses Monthly Active Rows (MAR) to calculate usage, just like any other Fivetran connector.

To calculate the MAR for a table in your Connector SDK, you can refer to How to Count Daily MAR Usage per Table troubleshooting article.

How is support handled for Connector SDK?

When you submit a ticket through our Support portal, our Support Team will triage the ticket.

• If the issue is with the Fivetran platform, our Support Team will work with you on the issue through resolution.
• If the issue is with the connection’s custom code or logic, our Professional Services Team can assist you, see Can you help me write a custom connector using the Connector SDK.

NOTE: The scope of our Customer Support Team's assistance is limited when it comes to troubleshooting custom code issues.

Can you help me write a custom connector using the Connector SDK?

Yes. If you need assistance in developing a custom Connector SDK connector, our Services team is happy to help. Contact your Account Representative to use existing service hours you may already have or submit a support request to get started with our Services team.