How to load data from MySQL to Clickhouse

Learn how to use Airbyte to synchronize your MySQL data into Clickhouse 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 MySQL connector in Airbyte

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

Set up Clickhouse for your extracted MySQL 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 MySQL to Clickhouse 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.

Demo video of Airbyte Cloud

Demo video of AI Connector Builder

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

Learn more
Chase Zieman headshot

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.”

Learn more

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."

Learn more

How to Sync to Manually

Step 1: Export Data from MySQL

Prerequisites

  • Ensure you have administrative access to the MySQL database.
  • Install ClickHouse server and client on the destination machine.
  • Familiarity with SQL and command-line tools.
  1. Connect to MySQL:
    Open a terminal and connect to your MySQL database using the following command:
    mysql -u [username] -p[password] [database_name]
    Replace `[username]`, `[password]`, and `[database_name]` with your MySQL credentials and database name.
  2. Choose Data to Export:
    Decide which tables or data you want to export. You can export entire tables or a subset of data based on your requirements.
  3. Export Data to CSV:
    Use the SELECT ... INTO OUTFILE statement to export the data to a CSV file. For example:
    SELECT * INTO OUTFILE '/path/to/your/output.csv'
    FIELDS TERMINATED BY ','
    OPTIONALLY ENCLOSED BY '"'
    LINES TERMINATED BY '\n'
    FROM your_table;

Replace `/path/to/your/output.csv` with the desired output file path and `your_table` with the table name you want to export.

Step 2: Prepare Data for ClickHouse

  1. Review Data Types:
    Ensure that the MySQL data types are compatible with ClickHouse data types. You may need to convert certain data types to match ClickHouse’s requirements.
  2. Modify CSV (if necessary):
    If any modifications are needed (e.g., changing date formats or handling NULL values), process the CSV file using a scripting language like Python or a tool like awk.
  3. Split Large Files (optional):
    If the CSV file is very large, consider splitting it into smaller chunks to make the import process more manageable.

Step 3: Create the Corresponding Table in ClickHouse

  1. Connect to ClickHouse:
    Open a terminal and connect to ClickHouse using the ClickHouse client:
    clickhouse-client -u [username] --password [password] --database [database_name]
    Replace [username], [password], and [database_name] with yourClickHouse credentials and database name.
  2. Create Table:
    Define the table schema in ClickHouse to match the structure of the MySQL data you are importing. Use the CREATE TABLE statement to create the table. For example:
    CREATE TABLE my_table (
    id UInt32,
    name String,
    created_at DateTime
    ) ENGINE = MergeTree()
    ORDER BY id;

Adjust the table definition according to your data.

Step 4: Import Data into ClickHouse

  1. Import Data:
    Use the clickhouse-client command to import the CSV file into ClickHouse. For example:
    clickhouse-client --query="INSERT INTO my_table FORMAT CSV" --database=[database_name] < /path/to/your/output.csv

    Replace [database_name] with your ClickHouse database name and /path/to/your/output.csv with the path to your CSV file.

Step 5: Verify Data Integrity

  1. Check Data Count:
    Run a simple SELECT COUNT(*) FROM my_table; query in both MySQL and ClickHouse to ensure that the row counts match.
  2. Compare Sample Data:
    Compare a sample set of data from both databases to verify that the data has been transferred correctly.
  3. Validate Data Types:
    Ensure that all data types have been correctly interpreted and stored in ClickHouse.

Step 6: Post-Import Cleanup

  1. Optimize Table (if necessary):
    In ClickHouse, you can run OPTIMIZE TABLE my_table FINAL; to merge data parts and improve query performance.
  2. Remove Temporary Files:
    Delete the CSV files if they are no longer needed to free up space.

Tips:

  • Always back up your data before performing migration operations.
  • Test the migration process with a small subset of data before moving the entire dataset.
  • Consider the impact of timezone differences and character encoding between MySQL and ClickHouse.
  • If you encounter performance issues, you can tweak ClickHouse settings or adjust the import process (e.g., using parallel imports).