The good performance. The nice graphical management console. The long list of ML algorithms.
Apache Spark excels in performance due to its in-memory processing and distributed computing, enabling faster data computing. It supports machine learning, streaming, and scalability, suitable for large datasets. User-friendly SQL compliance and flexible APIs aid integration, while extensive libraries offer high ROI. Challenges include tuning stability between APIs, limited programming language support, and improving connectors for cloud databases, with a significant learning curve and the need for more machine learning algorithm support.
