Which programming languages does Databricks support?

Databricks supports a variety of programming languages that are particularly suited for data analytics and machine learning tasks. The correct response indicates that Databricks natively supports Python, Scala, R, and SQL.

Python is widely used in data science for its simplicity and powerful libraries like Pandas, NumPy, and Scikit-learn. Scala is important within the Apache Spark ecosystem, as many of Spark's core functionalities are implemented in Scala, making it a preferred choice for performance-intensive applications. R, a language designed specifically for statistics and data visualization, is also integrated within Databricks, enabling data scientists to leverage its statistical capabilities. SQL is included for users who want to perform data queries and manipulation using a familiar structured query language, making it accessible for analysts who may not be proficient in other programming languages.

The other options list languages that are not aligned with the primary focus of Databricks on data processing and analytics. For example, C++ and Java are not primary languages used in the Databricks environment, and languages like Ruby, JavaScript, and C# do not serve the same purpose in the context of data science workflows. Additionally, C, C++, Python, and HTML do not provide the same level of support for integrated