It is primarily designed for data storage, offering high durability and availability.

It provides a unified programming model that supports both batch and stream processing, along with auto-scaling capabilities to handle varying workloads efficiently.

It offers a drag-and-drop visual interface for pipeline design, making it accessible to users without programming skills.

It is optimized for deploying and managing machine learning models, including features for model training and evaluation.

It integrates seamlessly with other GCP services like BigQuery, Cloud Storage, and Pub/Sub, enhancing its utility in data processing tasks.