TL;DR

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 ClickHouse as a source connector (using Auth, or usually an API key)
2. set up DuckDB 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 ClickHouse

An open-source database management system for online analytical processing (OLAP), ClickHouse takes the innovative approach of using a column-based database. It is easy to use right out of the box and is touted as being hardware efficient, extremely reliable, linearly scalable, and “blazing fast”—between 100-1,000x faster than traditional databases that write rows of data to the disk—allowing analytical data reports to be generated in real-time.

What is DuckDB

DuckDB is an in-process SQL OLAP database management system. It has strong support for SQL. DuckDB is borrowing the SQLite shell implementation. Each database is a single file on disk. It’s analogous to “ SQLite for analytical (OLAP) workloads” (direct comparison on the SQLite vs DuckDB paper here), whereas SQLite is for OLTP ones. But it can handle vast amounts of data locally. It’s the smaller, lighter version of Apache Druid and other OLAP technologies.

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Prerequisites

1. A ClickHouse account to transfer your customer data automatically from.
2. A DuckDB 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 ClickHouse and DuckDB, for seamless data migration.

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

Methods to Move Data From Clickhouse to duckdb

• Method 1: Connecting Clickhouse to duckdb using Airbyte.
• Method 2: Connecting Clickhouse to duckdb manually.

Method 1: Connecting Clickhouse to duckdb using Airbyte

Step 1: Set up ClickHouse as a source connector

1. First, navigate to the Airbyte dashboard and click on the "Destinations" tab on the left-hand side of the screen.
2. Next, click on the "Add Destination" button in the top right corner of the screen.
3. Select "ClickHouse" from the list of available destinations.
4. Enter the necessary information for your ClickHouse database, including the host, port, username, and password.
5. Choose the database and table you want to connect to from the dropdown menus.
6. Configure any additional settings, such as the batch size or maximum number of retries.
7. Test the connection to ensure that everything is working properly.
8. Once you have successfully connected to your ClickHouse database, you can begin syncing data from your source connectors to your ClickHouse destination.

Step 2: Set up DuckDB as a destination connector

1. Open the Airbyte platform and navigate to the "Destinations" tab on the left-hand side of the screen.
2. Click on the "Add Destination" button located in the top right corner of the screen.
3. Scroll down the list of available destinations until you find "DuckDB" and click on it.
4. Fill in the required information for your DuckDB database, including the host, port, database name, username, and password.
5. Test the connection to ensure that the information you provided is correct and that Airbyte can successfully connect to your DuckDB database.
6. If the connection is successful, click on the "Save" button to save your DuckDB destination connector.
7. You can now use this connector to transfer data from your source connectors to your DuckDB database. Simply select the DuckDB destination connector when setting up your data integration pipelines in Airbyte.

Step 3: Set up a connection to sync your ClickHouse data to DuckDB

Once you've successfully connected ClickHouse as a data source and DuckDB 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 ClickHouse from the dropdown list of your configured sources.
3. Select your destination: Choose DuckDB 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 ClickHouse objects you want to import data from towards DuckDB. 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 ClickHouse to DuckDB according to your settings.

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

Method 2: Connecting Clickhouse to duckdb manually

To move data from ClickHouse to DuckDB without using third-party connectors or integrations, you'll have to manually extract the data from ClickHouse and then import it into DuckDB. Here's a step-by-step guide to accomplish this:

Step 1: Export Data from ClickHouse

1. Access ClickHouse: Log in to the ClickHouse server through the command line or a database management tool.

2. Select Data: Decide which tables or data you want to export from ClickHouse.

3. Export Data to CSV:

   - Use the ClickHouse client to run a query that exports the data to a CSV file. Here's an example command that you can modify according to your needs:

     ```

     clickhouse-client --query="SELECT * FROM your_database.your_table FORMAT CSV" > /path/to/your_data.csv

     ```

   - Make sure to replace `your_database.your_table` with the appropriate database and table name, and `/path/to/your_data.csv` with the desired file path.

Step 2: Prepare Data (Optional)

1. Inspect the CSV File: Open the CSV file to ensure the data has been exported correctly. Look for any anomalies or export errors.

2. Clean and Transform: If necessary, clean the data or transform it to match the schema expected by DuckDB. You can use tools like sed, awk, or a programming language like Python to automate this process.

Step 3: Install and Set Up DuckDB

1. Install DuckDB: If you haven't already, download and install DuckDB. You can find the installation instructions on the [official DuckDB website](https://duckdb.org/docs/installation).

2. Initialize DuckDB: Start DuckDB and create a new database or connect to an existing one.

Step 4: Import Data into DuckDB

1. Prepare the Table Schema:

   - If the table doesn't exist in DuckDB, you'll need to create it with the appropriate schema to match the data you're importing from ClickHouse. Use the `CREATE TABLE` statement to define the table structure.

   - For example:

     ```

     CREATE TABLE your_table (

       column1 TYPE,

       column2 TYPE,

       ...

     );

     ```

   - Replace `TYPE` with the corresponding data types that match your CSV data.

2. Import Data:

   - Use the `COPY` command in DuckDB to import the data from the CSV file into the table you've created.

   - Here's an example command:

     ```

     COPY your_table FROM '/path/to/your_data.csv' (FORMAT CSV, HEADER);

     ```

   - Make sure to specify the correct path to your CSV file and any additional options you might need, such as specifying a delimiter if it's not a comma.

3. Verify the Import: After the data has been imported, run a few queries to ensure that the data is correctly loaded and the table behaves as expected.

Step 5: Clean Up

1. Remove Temporary Files: If you created any temporary files or used any scripts for data transformation, clean them up to avoid clutter and potential data leaks.

2. Backup: If necessary, create a backup of the newly imported data in DuckDB.

By following these steps, you should be able to move data from ClickHouse to DuckDB without the need for third-party connectors or integrations. Remember to handle data types and potential differences in SQL dialects between the two databases carefully. Always verify the imported data to ensure integrity and consistency.

Use Cases to transfer your ClickHouse data to DuckDB

Integrating data from ClickHouse to DuckDB provides several benefits. Here are a few use cases:

1. Advanced Analytics: DuckDB’s powerful data processing capabilities enable you to perform complex queries and data analysis on your ClickHouse data, extracting insights that wouldn't be possible within ClickHouse alone.
2. Data Consolidation: If you're using multiple other sources along with ClickHouse, syncing to DuckDB allows you to centralize your data for a holistic view of your operations, and to set up a change data capture process so you never have any discrepancies in your data again.
3. Historical Data Analysis: ClickHouse has limits on historical data. Syncing data to DuckDB allows for long-term data retention and analysis of historical trends over time.
4. Data Security and Compliance: DuckDB provides robust data security features. Syncing ClickHouse data to DuckDB ensures your data is secured and allows for advanced data governance and compliance management.
5. Scalability: DuckDB can handle large volumes of data without affecting performance, providing an ideal solution for growing businesses with expanding ClickHouse data.
6. Data Science and Machine Learning: By having ClickHouse data in DuckDB, you can apply machine learning models to your data for predictive analytics, customer segmentation, and more.
7. Reporting and Visualization: While ClickHouse provides reporting tools, data visualization tools like Tableau, PowerBI, Looker (Google Data Studio) can connect to DuckDB, providing more advanced business intelligence options. If you have a ClickHouse table that needs to be converted to a DuckDB table, Airbyte can do that automatically.

Wrapping Up

To summarize, this tutorial has shown you how to:

1. Configure a ClickHouse account as an Airbyte data source connector.
2. Configure DuckDB as a data destination connector.
3. Create an Airbyte data pipeline that will automatically be moving data directly from ClickHouse to DuckDB 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!