Simplifying Real-Time Analytics on JSON: Capella Columnar vs. ClickHouse

Ensuring a seamless flow of data is crucial for effective analysis and decision-making, particularly when it comes to handling unstructured and nested data structures in databases like MongoDB. To achieve this, we explored the process of data ingestion from MongoDB into both ClickHouse, a relational database, and Couchbase Capella Columnar, a NoSQL analytical database. We found that Capella Columnar simplifies working with nested data by not requiring preprocessing for nested data, allowing direct ingestion from MongoDB collections without separate tables or joins. In contrast, ClickHouse requires extensive preprocessing due to the unnesting of nested data, adding new fields necessitating additional table creation and schema updates. Real-time data changes in Capella Columnar are automatically reflected without additional processing, whereas ClickHouse faces challenges with pipeline breaks and manual intervention required for managing these changes. Overall, Couchbase Capella offers a more streamlined approach to handling complex, nested structures, making it the more flexible and efficient choice for environments dealing with real-time data and nested formats.