How to load data from DynamoDB to Clickhouse

Learn how to use Airbyte to synchronize your DynamoDB data into Clickhouse within minutes.

Try Airbyte Cloud Manual method (the hard way)

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Start syncing with Airbyte in 3 easy steps within 10 minutes

Set up a DynamoDB 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 DynamoDB 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 DynamoDB 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.

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How to Sync to Manually

Step 1: Set Up Your Environment

Prepare your development environment by installing necessary tools. You will need the AWS SDK for your preferred programming language (e.g., Python, Node.js) to interact with DynamoDB and a ClickHouse client to interact with the ClickHouse database. Install the AWS CLI for easier configuration and testing.

Step 2: Extract Data from DynamoDB

Write a script to extract data from your DynamoDB table. Use the AWS SDK to scan or query the table based on your requirements. Be mindful of DynamoDB's limitations on data retrieval (e.g., read capacity units, pagination). If your data set is large, consider using DynamoDB Streams or breaking the data extraction into smaller chunks.

Step 3: Transform Data to ClickHouse Format

Once data is extracted, transform it into a format suitable for ClickHouse. This typically involves converting JSON data (common in DynamoDB) into CSV or TSV format, which ClickHouse can ingest efficiently. Ensure data types are compatible with the ClickHouse schema.

Step 4: Prepare ClickHouse Database

Set up the necessary tables in ClickHouse to store the data. Define the schema based on the transformed data. Ensure that the columns and data types match those of the incoming data. Use the ClickHouse client or SQL interface to create tables.

Step 5: Load Data into ClickHouse

Use the ClickHouse client to load the data into your ClickHouse tables. You can use the `INSERT INTO` command if the data set is small or the `INSERT INTO ... FORMAT CSV` command for bulk loading when dealing with larger datasets. Make sure to handle data types and potential errors during the import process.

Step 6: Verify Data Integrity

After loading data into ClickHouse, perform checks to ensure data integrity. Compare the record counts and sample data between DynamoDB and ClickHouse to ensure accuracy. Use SQL queries to validate data in ClickHouse and ensure there are no discrepancies.

Step 7: Automate the Process

Once the manual process is successful, automate the data transfer using a script. This script should handle data extraction, transformation, and loading (ETL) and can be scheduled using cron jobs or any other scheduling tool. Ensure error handling and logging are implemented to facilitate monitoring and troubleshooting.
By following these steps, you can systematically move data from DynamoDB to ClickHouse without relying on third-party connectors or integrations.