How to load data from Commcare to Weaviate

Learn how to use Airbyte to synchronize your Commcare data into Weaviate within minutes.

Building your pipeline or Using Airbyte

Airbyte is the only open source solution empowering data teams  to meet all their growing custom business demands in the new AI era.

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.

After Airbyte

Airbyte connections are:
  • Reliable and accurate
  • Extensible and scalable for all your needs
  • Deployed and governed your way
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 Commcare connector in Airbyte

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

Set up Weaviate for your extracted Commcare 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 Commcare to Weaviate 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.

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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Setup Complexities simplified!

You don’t need to put hours into figuring out how to use Airbyte to achieve your Data Engineering goals.

Simple & Easy to use Interface

Airbyte is built to get out of your way. Our clean, modern interface walks you through setup, so you can go from zero to sync in minutes—without deep technical expertise.

Guided Tour: Assisting you in building connections

Whether you’re setting up your first connection or managing complex syncs, Airbyte’s UI and documentation help you move with confidence. No guesswork. Just clarity.

Airbyte AI Assistant that will act as your sidekick in building your data pipelines in Minutes

Airbyte’s built-in assistant helps you choose sources, set destinations, and configure syncs quickly. It’s like having a data engineer on call—without the overhead.

What sets Airbyte Apart

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.

An Extensible Open-Source Standard

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.

Full Control & Security

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.

Enterprise Support with SLAs

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: Export Data from CommCare

Start by exporting the data you need from CommCare. Navigate to the CommCare HQ dashboard, select the project space, and access the "Data" section. Use the "Export Data" feature to create a form or case export, depending on your data type. Set your export parameters, and download the CSV file to your local machine.

Step 2: Install Weaviate

Ensure that Weaviate is installed locally or on a server where you can access it. You can install Weaviate using Docker. Pull the latest Weaviate image using the command: `docker pull semitechnologies/weaviate:latest`, and start it using Docker Compose or a simple Docker run command. Ensure that it's running by accessing its RESTful API endpoint.

Step 3: Define Weaviate Schema

Access the Weaviate dashboard or utilize the REST API to create a schema that matches the structure of your data. The schema defines classes and properties that your data will map to. Use the Weaviate API to POST the schema definitions, ensuring you define the data types and relationships correctly.

Step 4: Prepare Data for Import

Convert your exported CSV data into a JSON format that matches your Weaviate schema. Use Python or another programming language to script this conversion. Ensure that each data entry in JSON corresponds to a class in your Weaviate schema, with properties correctly mapped.

Step 5: Import Data into Weaviate

Use the Weaviate REST API to import the data. Write a script that iterates over your JSON data and sends POST requests to Weaviate's `/objects` endpoint. Ensure each object is correctly formatted according to your defined schema, and handle any API responses to confirm that the data is imported successfully.

Step 6: Verify Data Integrity

After importing, verify that the data in Weaviate matches what was exported from CommCare. Use the Weaviate API to query the data and check the integrity and accuracy against your original dataset. Look for any discrepancies or missing entries and rectify them by re-importing the specific data entries.

Step 7: Optimize Performance and Query Data

Once data integrity is confirmed, optimize Weaviate for performance. Adjust settings such as replication and sharding if needed. Familiarize yourself with Weaviate's querying capabilities to access your data efficiently. Use GraphQL or RESTful queries to retrieve and manipulate data as required for your application or analysis.

By following these steps, you'll be able to successfully move data from CommCare to Weaviate without relying on third-party connectors or integrations.