When it comes to data warehousing, both MongoDB and ClickHouse have their own strengths and differences. Let's explore these differences and determine which one is better suited for a data warehouse.

MongoDB
MongoDB is a popular NoSQL database that offers flexibility and scalability. It stores data in JSON-like documents, making it easy to work with unstructured or semi-structured data. MongoDB is known for its ability to handle high volumes of data and its horizontal scalability.
One of the key advantages of MongoDB for data warehousing is its flexibility in schema design. It allows you to store data without a predefined schema, which can be useful when dealing with rapidly changing or evolving data structures. For example, if you have a data warehouse that needs to accommodate frequent changes in data structure, MongoDB can be a good choice.
However, MongoDB may not be suitable for all data warehousing scenarios. Since it doesn't support joins or transactions natively, complex analytical queries can be challenging to perform efficiently. Additionally, MongoDB may not be the best option for data warehouses that require strict consistency and ACID (Atomicity, Consistency, Isolation, Durability) properties.

ClickHouse
ClickHouse, on the other hand, is a columnar database specifically designed for online analytical processing (OLAP). It excels at executing complex analytical queries and aggregations on large datasets with high performance.
ClickHouse organizes data by columns rather than rows, which allows for efficient compression and query execution. It supports a wide range of analytical functions and has extensive support for distributed query execution. ClickHouse is known for its ability to handle massive amounts of data and provide real-time analytics.
If your data warehouse primarily focuses on running complex analytical queries and aggregations, ClickHouse can be a great choice. It provides excellent performance and scalability for OLAP workloads. However, if your data warehouse requires flexible schema design or frequent data structure changes, ClickHouse may not be the ideal option.

Conclusion
Choosing between MongoDB and ClickHouse for a data warehouse depends on your specific requirements. MongoDB offers flexibility and scalability, making it suitable for scenarios with evolving data structures. ClickHouse, on the other hand, excels at complex analytical queries and provides high performance for OLAP workloads.
It's important to evaluate your data warehousing needs and consider factors such as data structure, query complexity, scalability, and performance before making a decision. Additionally, it can be beneficial to benchmark and test both databases with your specific workload to determine which one performs better for your use case.
References:
MongoDB
ClickHouse