How to load data from Harvest to Convex

Learn how to use Airbyte to synchronize your Harvest data into Convex within minutes.

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Furthermore, you will need to build and maintain Y x Z pipelines with Y sources and Z destinations to cover all your needs.
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Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Harvest connector in Airbyte

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

Set up Convex for your extracted Harvest 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 Harvest to Convex 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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Check out our interactive demo and our how-to videos to learn how you can sync data from any source to any destination.

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How to Sync to Manually

Step 1: Export Data from Harvest

Begin by exporting the data you need from Harvest. Navigate to the Harvest application, and use the export feature to download your data in a CSV format. This feature is typically found under the reports or data management section. Ensure that the export includes all necessary fields and records you require.

Open the exported CSV file with a spreadsheet application like Microsoft Excel or Google Sheets. Review the data to confirm that all required fields are included and that the data is clean and well-organized. Make any necessary adjustments, such as correcting data formats or removing unwanted fields.

Before importing data into Convex, ensure that your Convex environment is set up properly. This includes configuring your database schema to match the data structure of the CSV file. Create any necessary tables or fields in Convex that correspond to the data you are importing.

Since Convex often works with JSON for data operations, convert your CSV file into a JSON format. You can do this manually by writing a script in Python or using a spreadsheet tool to export the data as JSON. Ensure that the JSON structure aligns with the schema of your Convex database.

To interact with Convex, you need to authenticate using their API. Obtain the necessary API keys or tokens from your Convex account settings. This will allow you to programmatically access and update your Convex database.

Create a script in a programming language such as Python or JavaScript to read the JSON file and make API calls to Convex. The script should iterate over each record in the JSON file and use HTTP POST or PUT requests to insert the data into the appropriate Convex tables. Ensure you handle any API response errors and log the import process for troubleshooting.

Once the data is imported, verify that the data in Convex matches the original data from Harvest. This can be done by running queries in Convex to check counts, values, and data consistency. If discrepancies are found, troubleshoot the import script or data preparation steps and repeat the process as necessary until the data is accurately transferred.

By following these steps, you can effectively move data from Harvest to Convex without relying on third-party connectors or integrations.