How to load data from Jenkins to Weaviate

Learn how to use Airbyte to synchronize your Jenkins 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 Jenkins 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 Jenkins 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 Jenkins 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: Set Up Jenkins Job for Data Export

Begin by configuring a Jenkins job that will handle the data export. Ensure that Jenkins has access to the data you wish to transfer. Use Jenkins' built-in capabilities to access and format the data, such as using shell scripts or Groovy scripts for data extraction and conversion into a format suitable for transfer (e.g., JSON or CSV).

Step 2: Prepare Data for Transfer

In the Jenkins job, process the extracted data to match the Weaviate schema requirements. This may involve transforming the data into JSON format and ensuring it includes the necessary properties and structures expected by Weaviate, like class names, properties, and data types.

Step 3: Install HTTP Client in Jenkins

Make sure Jenkins has an HTTP client available for sending HTTP requests. You can use command-line tools like `curl` or `httpie`, which can be executed within a Jenkins job. If these tools are not installed, you may need to add a step in your Jenkins job to install them.

Step 4: Configure Authentication for Weaviate API

Determine the authentication method required by your Weaviate instance (e.g., API keys, tokens). Securely store any authentication credentials in Jenkins using the credentials plugin. Reference these credentials in your Jenkins job to ensure secure access to the Weaviate API.

Step 5: Create a Weaviate Import Script

Write a script within your Jenkins job to handle the POST requests to the Weaviate API. This script should read the prepared data and send it to the correct endpoint in Weaviate. Ensure that your script handles the Weaviate classes and properties correctly, and make use of error handling to catch any issues during the transfer.

Step 6: Execute the Jenkins Job for Data Transfer

Run the Jenkins job to execute the entire process. This includes exporting the data, transforming it, and then sending it to Weaviate. Monitor the job's output for any errors or warnings that could indicate issues with data formatting, connectivity, or authentication.

Step 7: Verify Data in Weaviate

After the job completes, verify that the data has been successfully transferred to Weaviate. Use the Weaviate console or API to check that the data is present and correctly structured according to your needs. If discrepancies are found, adjust the Jenkins job and scripts as necessary and re-run the process until the data transfer is satisfactory.