How to load data from Hubplanner to Kafka

Learn how to use Airbyte to synchronize your Hubplanner data into Kafka within minutes.

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Set up a Hubplanner connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Kafka for your extracted Hubplanner data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Hubplanner to Kafka in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.
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How to Sync to Manually

Step 1: Understand HubPlanner API Capabilities

Begin by thoroughly reviewing the HubPlanner API documentation to understand the data endpoints available. This includes identifying the required endpoints to extract the data you need, the authentication method used (typically API key or OAuth), and any rate limits or pagination requirements the API might enforce.

Install and configure a local Kafka environment if you haven't already. This involves downloading Kafka, setting up ZooKeeper (required for Kafka), and starting the Kafka server. Ensure that your Kafka setup is running smoothly and is ready to receive messages.

Write a script in a programming language you are comfortable with (e.g., Python, Node.js) to extract data from HubPlanner. Use HTTP requests to connect to HubPlanner's API, authenticate, and fetch the desired data. Handle any API pagination by implementing a loop to retrieve all data pages if necessary.

Once data is extracted, transform it into a format suitable for Kafka. Kafka typically handles data in JSON or Avro formats. Ensure that your data transformation script converts the data into one of these formats, maintaining any necessary data structures and field names.

To send data to Kafka, install a Kafka producer library for your scripting language (e.g., `kafka-python` for Python or `kafkajs` for Node.js). This library will facilitate communication with your Kafka broker, allowing your script to publish messages to specific Kafka topics.

Use the Kafka producer library to send the transformed data to a Kafka topic. Ensure that you handle any potential errors, such as network issues or Kafka broker unavailability, by implementing retries or logging errors for later review. Define whether the data should be sent synchronously or asynchronously based on your requirements.

Set up a Kafka consumer on another script or tool to verify that the data is being correctly received in Kafka. This consumer should subscribe to the same topic(s) to which your producer is sending data. Monitor the Kafka logs and the consumer output to ensure the data transfer is successful and consistent.

By following these steps, you can effectively move data from HubPlanner to Kafka using custom scripts and direct API interactions, without relying on third-party connectors or integrations.