Summarize this article with:
Trusted by data-driven companies
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.
- Inconsistent and inaccurate data
- Laborious and expensive
- Brittle and inflexible
- Reliable and accurate
- Extensible and scalable for all your needs
- Deployed and governed your way
Start syncing with Airbyte in 3 easy steps within 10 minutes
Take a virtual tour
Demo video of Airbyte Cloud
Demo video of AI Connector Builder
Setup Complexities simplified!
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
Move Large Volumes, Fast
An Extensible Open-Source Standard
Full Control & Security
Fully Featured & Integrated
Enterprise Support with SLAs
What our users say
Andre Exner
"For TUI Musement, Airbyte cut development time in half and enabled dynamic customer experiences."
Chase Zieman
“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.”
Rupak Patel
"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."
Start by familiarizing yourself with Recruitee's API documentation. This understanding will help you know how to authenticate and fetch the necessary data. Recruitee's API allows you to access candidate data, job details, and other recruitment-related information.
Recruitee uses API keys for authentication. Create or locate your API key within your Recruitee account settings. Use this API key in your HTTP requests to authenticate and access the Recruitee API securely. Make sure to keep your API key confidential.
Develop a script or program using a programming language like Python to make HTTP GET requests to Recruitee's API endpoints. Specify the endpoint for the data you need (e.g., candidates, job offers) and include your API key in the request headers. Parse the JSON response to extract the data you wish to transfer.
Install RabbitMQ on your server or local machine from the official RabbitMQ website. Once installed, configure RabbitMQ to suit your requirements. You can use the RabbitMQ Management Console to create a new queue where the data from Recruitee will be sent.
Using a programming language like Python and the Pika library, write a script that connects to your RabbitMQ instance. This script will publish messages to the RabbitMQ queue. Ensure that the script formats the data fetched from Recruitee into a suitable message format (e.g., JSON) before publishing.
Execute your scripts to test the data transfer process. First, run the script to fetch data from Recruitee and publish it to RabbitMQ. Then, verify that the messages have been successfully added to the RabbitMQ queue by checking through the RabbitMQ Management Console or by consuming the messages with a simple consumer script.
Once the data transfer process is working smoothly, automate it by scheduling the scripts to run at regular intervals using a task scheduler like cron (Linux) or Task Scheduler (Windows). This automation will ensure that data is regularly moved from Recruitee to RabbitMQ without manual intervention.
By following these steps, you can effectively transfer data from Recruitee to RabbitMQ without relying on third-party connectors or integrations.
FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
Recruitee is the collaborative hiring software that delivers a complete solution to help internal teams hire better together. As an Applicant Tracking System, it enables recruitment teams to easily manage the hiring process from start to finish while keeping hiring managers and colleagues as active participants. Recruitee is on a mission to empower teams with the best tech tools to hire better together. Its vision is to put collaboration at the core of hiring teams.
Recruitee's API provides access to a wide range of data related to recruitment and hiring processes. The following are the categories of data that can be accessed through the API:
1. Candidates: Information about candidates who have applied for a job, including their name, contact details, resume, and application status.
2. Jobs: Details about job openings, including the job title, description, location, and requirements.
3. Applications: Data related to the application process, such as the date and time of application, the source of the application, and the status of the application.
4. Users: Information about users who have access to the Recruitee account, including their name, email address, and role.
5. Teams: Details about teams within the organization, including the team name, members, and permissions.
6. Stages: Information about the different stages of the recruitment process, such as screening, interviewing, and hiring.
7. Tags: Data related to tags that can be assigned to candidates, jobs, and applications to help with organization and filtering.
8. Custom fields: Information about custom fields that can be added to candidates, jobs, and applications to capture additional data.
Overall, the Recruitee API provides a comprehensive set of data that can be used to streamline recruitment processes and improve hiring outcomes.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey:
