How to load data from Public Apis to Convex

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

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Building in-house pipelines
Bespoke pipelines are:
  • Inconsistent and inaccurate data
  • Laborious and expensive
  • Brittle and inflexible
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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Airbyte connections are:
  • Reliable and accurate
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All your pipelines in minutes, however custom they are, thanks to Airbyte’s connector marketplace and AI Connector Builder.

Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a Public Apis 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 Public Apis 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 Public Apis 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.
Try Airbyte CloudManual method (the hard way)

Take a virtual tour

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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Modern GenAI Workflows

Streamline AI workflows with Airbyte: load unstructured data into vector stores like Pinecone, Weaviate, and Milvus. Supports RAG transformations with LangChain chunking and embeddings from OpenAI, Cohere, etc., all in one operation.

Move Large Volumes, Fast

Quickly get up and running with a 5-minute setup that enables both incremental and full refreshes for databases of any size, seamlessly scaling to handle large data volumes. Our optimized architecture overcomes performance bottlenecks, ensuring efficient data synchronization even as your datasets grow from gigabytes to petabytes.

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More than 1,000 developers contribute to Airbyte’s connectors, different interfaces (UI, API, Terraform Provider, Python Library), and integrations with the rest of the stack. Airbyte’s AI Connector Builder lets you edit or add new connectors in minutes.

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Airbyte secures your data with cloud-hosted, self-hosted or hybrid deployment options. Single Sign-On (SSO) and Role-Based Access Control (RBAC) ensure only authorized users have access with the right permissions. Airbyte acts as a HIPAA conduit and supports compliance with CCPA, GDPR, and SOC2.

Fully Featured & Integrated

Airbyte automates schema evolution for seamless data flow, and utilizes efficient Change Data Capture (CDC) for real-time updates. Select only the columns you need, and leverage our dbt integration for powerful data transformations.

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Airbyte Self-Managed Enterprise comes with dedicated support and guaranteed service level agreements (SLAs), ensuring that your data movement infrastructure remains reliable and performant, and expert assistance is available when needed.

What our users say

Raman Singh

Tech Lead at Symend

Predictable, straightforward pricing model that simplified budgeting and significantly reduced overall spend

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Chase Zieman

Chief Data Officer

“Airbyte helped us accelerate our progress by years, compared to our competitors. We don’t need to worry about connectors and focus on creating value for our users instead of building infrastructure. That’s priceless. The time and energy saved allows us to disrupt and grow faster.”

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Rupak Patel

Operational Intelligence Manager

"With Airbyte, we could just push a few buttons, allow API access, and bring all the data into Google BigQuery. By blending all the different marketing data sources, we can gain valuable insights."

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How to Sync to Manually

Step 1: Understand the Data Requirements

Begin by identifying the specific data you need from the public API and how it should be structured in Convex. This includes understanding the data types, schema, and any relationships or constraints that must be maintained.

Obtain access to the public API by reviewing its documentation. You'll need to note the API's endpoints, authentication requirements (if any), and data format (typically JSON or XML). Make sure you have any necessary API keys or credentials.

Use a programming language like JavaScript or Python to fetch data from the API. You can use the `fetch` method in JavaScript or `requests` in Python to make HTTP requests to the API endpoints. Ensure you handle any pagination if the API returns data in pages.

Once the data is fetched, transform it into the structure expected by Convex. This may involve renaming fields, converting data types, and filtering out unnecessary information. Use functions or scripts to automate this process and ensure data consistency.

On the Convex platform, define the schema that will hold your data. This involves creating tables and specifying the fields, data types, and any relationships or constraints. This step ensures Convex is ready to store the incoming data.

Write a script or program to insert the transformed data into Convex using its API or SDK. This typically involves making HTTP POST requests with the data payload to Convex's data endpoints. Use loops or batch processing to handle large datasets efficiently.

After the data is uploaded, perform checks to ensure it has been transferred accurately and completely. This can include comparing sample records between the API and Convex, and setting up monitoring to alert you to any future discrepancies or issues with the data transfer process.

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