What kind of applications can be developed on Databricks?

Databricks is a versatile platform that supports a wide range of applications beyond just data storage. The ability to develop applications for Extract, Transform, Load (ETL) processes, data science projects, and machine learning is one of its primary strengths. Databricks provides a unified environment where users can leverage Apache Spark for processing large datasets, apply machine learning algorithms, and perform data analytics in a seamless workflow.

This platform is designed to facilitate data engineers and data scientists to collaborate effectively. It integrates with various data sources and tools, allowing the development of complex workflows that can ingest data, transform it, and apply statistical methods or machine learning models to extract insights. By supporting multiple languages and libraries, it enables users to implement a wide breadth of tasks within the realm of data handling and analysis.

In contrast, the other options are too restrictive. While Databricks does have capabilities for managing cloud resources, it is not limited to that function. The assertion that it supports only web applications or solely data storage applications overlooks its comprehensive framework for data processing and analysis, which is central to its utility in diverse workflows across industries.