Flattening DynamoDB JSON in ClickHouse

This text discusses how to unlock scalable analytics using DynamoDB data with ClickHouse through Propel's Serverless ClickHouse plan. It provides a step-by-step guide on flattening DynamoDB JSON data for more accessible analytics, including creating Materialized Views and handling single or multiple table designs. The process involves extracting specific fields from the nested JSON structure of DynamoDB events, casting various fields to appropriate data types, converting timestamps, preserving JSON objects, renaming fields, and flattening complex structures into a more queryable tabular format. Propel's Serverless ClickHouse plan offers true pay-per-query pricing and instant auto-scaling, making it an ideal solution for handling event-driven data architecture efficiently.