Final answer:
Data Lake is ideal for large distributed data storage because it can store a vast amount of raw data, including structured, semi-structured, and unstructured data. SQL database, Cosmos DB, and Blob Storage have different purposes and may not be as suitable for large distributed data storage.
Step-by-step explanation:
Data Lake is ideal for large distributed data storage. It is a repository that stores a vast amount of raw data, including structured, semi-structured, and unstructured data, in its native format. It provides a scalable and cost-effective solution for storing and analyzing big data.
SQL database is not ideal for large distributed data storage because it is designed for structured data and may have limitations in handling massive amounts of unstructured data.
Cosmos DB is a globally distributed, multi-model database service provided by Microsoft. While it is capable of storing large amounts of data, it is more suitable for operational and transactional workloads rather than serving as a dedicated large-scale data storage solution.
Blob Storage is a cloud storage service provided by Microsoft Azure that is designed to store unstructured data such as images, videos, and documents. While it can handle large amounts of data, it does not provide the same level of functionality and flexibility as Data Lake for distributed data analysis and processing.