Which programming language is primarily supported by Databricks?

Python is the primary language supported by Databricks due to its versatility and the extensive ecosystem of libraries available for data analysis and machine learning. Databricks provides robust support for various Python libraries such as Pandas, NumPy, and PySpark, which are commonly used for data manipulation, analysis, and processing large datasets. The integration of Python into the Databricks environment allows data analysts and data scientists to quickly prototype and implement data-driven solutions.

While Java is also supported, particularly for distributed computing with Apache Spark, Python has gained significant popularity among data professionals for its readability and ease of use, making it the preferred choice for many users in the Databricks ecosystem. Other languages like JavaScript and C++ are less commonly used in the context of data analysis within Databricks. JavaScript is more focused on web development, while C++ does not have the same level of library support for data analysis tasks. This makes Python the clear standout for users working within the Databricks platform.