Finance & Ops Analytics

How to load data from Zoom to MySQL

Learn how to use Airbyte to synchronize your Zoom data into MySQL within minutes.


This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps:

  1. set up Zoom as a source connector (using Auth, or usually an API key)
  2. set up MySQL as a destination connector
  3. define which data you want to transfer and how frequently

You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud.

This tutorial’s purpose is to show you how.

What is Zoom

Zoom offers a communications platform that connects people through video, voice, chat, and content sharing. It has an easy, reliable cloud platform for video and audio conferencing, collaboration, chat, and webinars across mobile devices, desktops, telephones, and room systems. Zoom unifies cloud video conferencing,simple online meetings, and group messaging into one easy-to-use platform. The company's mission is to create a people-centric cloud service that transforms the real-time collaboration experience and improves the quality and effectiveness of communications.

What is MySQL

MySQL is an SQL (Structured Query Language)-based open-source database management system. An application with many uses, it offers a variety of products, from free MySQL downloads of the most recent iteration to support packages with full service support at the enterprise level. The MySQL platform, while most often used as a web database, also supports e-commerce and data warehousing applications, and more.


  1. A Zoom account to transfer your customer data automatically from.
  2. A MySQL account.
  3. An active Airbyte Cloud account, or you can also choose to use Airbyte Open Source locally. You can follow the instructions to set up Airbyte on your system using docker-compose.

Airbyte is an open-source data integration platform that consolidates and streamlines the process of extracting and loading data from multiple data sources to data warehouses. It offers pre-built connectors, including Zoom and MySQL, for seamless data migration.

When using Airbyte to move data from Zoom to MySQL, it extracts data from Zoom using the source connector, converts it into a format MySQL can ingest using the provided schema, and then loads it into MySQL via the destination connector. This allows businesses to leverage their Zoom data for advanced analytics and insights within MySQL, simplifying the ETL process and saving significant time and resources.

Step 1: Set up Zoom as a source connector

1. Open the Airbyte platform and navigate to the "Sources" tab on the left-hand side of the screen.
2. Click on the "Add Source" button and select "Zoom" from the list of available connectors.
3. Enter your Zoom credentials, including your email address and password, in the appropriate fields.
4. Click on the "Test" button to ensure that your credentials are correct and that Airbyte can connect to your Zoom account.
5. Once the test is successful, click on the "Save" button to save your credentials and complete the connection process.
6. You can now configure your Zoom source connector by selecting the specific data you want to replicate and setting up any necessary filters or transformations.
7. Once you have configured your Zoom source connector, you can run a sync to start replicating data from your Zoom account to your destination data warehouse or data lake.

Step 2: Set up MySQL as a destination connector

1. First, you need to have a MySQL database set up and running. Ensure that you have the necessary credentials to access the database.
2. Log in to your Airbyte account and navigate to the "Destinations" tab.
3. Click on the "Add Destination" button and select "MySQL" from the list of available connectors.
4. Enter the necessary details such as the host, port, username, password, and database name. Ensure that the details are accurate and match the credentials you have for your MySQL database.
5. Test the connection to ensure that Airbyte can successfully connect to your MySQL database. If the connection is successful, you will receive a confirmation message.
6. Once the connection is established, you can configure the settings for your MySQL destination connector. You can choose to enable or disable certain features such as SSL encryption, bulk loading, and more.
7. You can also set up the schema mapping for your MySQL database. This involves mapping the fields from your source data to the corresponding fields in your MySQL database.
8. Once you have configured the settings and schema mapping, you can start syncing data from your source to your MySQL database. You can choose to run the sync manually or set up a schedule for automatic syncing.
9. Monitor the sync process to ensure that data is being transferred accurately and efficiently. You can view the sync logs and troubleshoot any issues that may arise.
10. Congratulations! You have successfully connected your MySQL destination connector on Airbyte and can now start syncing data from your source to your MySQL database.

Step 3: Set up a connection to sync your Zoom data to MySQL

Once you've successfully connected Zoom as a data source and MySQL as a destination in Airbyte, you can set up a data pipeline between them with the following steps:

  1. Create a new connection: On the Airbyte dashboard, navigate to the 'Connections' tab and click the '+ New Connection' button.
  2. Choose your source: Select Zoom from the dropdown list of your configured sources.
  3. Select your destination: Choose MySQL from the dropdown list of your configured destinations.
  4. Configure your sync: Define the frequency of your data syncs based on your business needs. Airbyte allows both manual and automatic scheduling for your data refreshes.
  5. Select the data to sync: Choose the specific Zoom objects you want to import data from towards MySQL. You can sync all data or select specific tables and fields.
  6. Select the sync mode for your streams: Choose between full refreshes or incremental syncs (with deduplication if you want), and this for all streams or at the stream level. Incremental is only available for streams that have a primary cursor.
  7. Test your connection: Click the 'Test Connection' button to make sure that your setup works. If the connection test is successful, save your configuration.
  8. Start the sync: If the test passes, click 'Set Up Connection'. Airbyte will start moving data from Zoom to MySQL according to your settings.

Remember, Airbyte keeps your data in sync at the frequency you determine, ensuring your MySQL data warehouse is always up-to-date with your Zoom data.

Use Cases to transfer your Zoom data to MySQL

Integrating data from Zoom to MySQL provides several benefits. Here are a few use cases:

  1. Advanced Analytics: MySQL’s powerful data processing capabilities enable you to perform complex queries and data analysis on your Zoom data, extracting insights that wouldn't be possible within Zoom alone.
  2. Data Consolidation: If you're using multiple other sources along with Zoom, syncing to MySQL allows you to centralize your data for a holistic view of your operations
  3. Historical Data Analysis: Zoom has limits on historical data. Syncing data to MySQL allows for long-term data retention and analysis of historical trends over time.
  4. Data Security and Compliance: MySQL provides robust data security features. Syncing Zoom data to MySQL ensures your data is secured and allows for advanced data governance and compliance management.
  5. Scalability: MySQL can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding Zoom data.
  6. Data Science and Machine Learning: By having Zoom data in MySQL, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
  7. Reporting and Visualization: While Zoom provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to MySQL, providing more advanced business intelligence options.

Wrapping Up

To summarize, this tutorial has shown you how to:

  1. Configure a Zoom account as an Airbyte data source connector.
  2. Configure MySQL as a data destination connector.
  3. Create an Airbyte data pipeline that will automatically be moving data directly from Zoom to MySQL after you set a schedule

With Airbyte, creating data pipelines take minutes, and the data integration possibilities are endless. Airbyte supports the largest catalog of API tools, databases, and files, among other sources. Airbyte's connectors are open-source, so you can add any custom objects to the connector, or even build a new connector from scratch without any local dev environment or any data engineer within 10 minutes with the no-code connector builder.

We look forward to seeing you make use of it! We invite you to join the conversation on our community Slack Channel, or sign up for our newsletter. You should also check out other Airbyte tutorials, and Airbyte’s content hub!

Frequently Asked Questions

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.

What data can you extract from Zoom?

Zoom's API provides access to a wide range of data related to Zoom meetings, webinars, users, and accounts. The following are the categories of data that can be accessed through Zoom's API:  

1. Meetings: Information related to Zoom meetings, such as meeting ID, topic, start and end time, duration, participants, and recording.  
2. Webinars: Data related to Zoom webinars, including webinar ID, topic, start and end time, duration, attendees, and recording.  
3. Users: Information about Zoom users, such as user ID, name, email address, and account type.  
4. Accounts: Data related to Zoom accounts, including account ID, name, email address, and billing information.  
5. Reports: Various reports related to Zoom meetings and webinars, such as attendance reports, participant reports, and usage reports.  
6. Recordings: Information related to Zoom meeting and webinar recordings, including recording ID, name, duration, and download links.  
7. Settings: Data related to Zoom account and meeting settings, such as default meeting settings, user settings, and account settings.  

Overall, Zoom's API provides a comprehensive set of data that can be used to analyze and optimize Zoom meetings and webinars, as well as manage Zoom accounts and users.

What data can you transfer to MySQL?

You can transfer a wide variety of data to MySQL. This usually includes structured, semi-structured, and unstructured data like transaction records, log files, JSON data, CSV files, and more, allowing robust, scalable data integration and analysis.

What are top ETL tools to transfer data from Zoom to MySQL?

The most prominent ETL tools to transfer data from Zoom to MySQL include:

  • Airbyte
  • Fivetran
  • Stitch
  • Matillion
  • Talend Data Integration

These tools help in extracting data from Zoom and various sources (APIs, databases, and more), transforming it efficiently, and loading it into MySQL and other databases, data warehouses and data lakes, enhancing data management capabilities.

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.