Excellent architectural features that are worth calling out, such as: Faster data access from partitioned memory grid Hot & cold optimized caching Ability to ingest real-time/historical data from diverse data sources such as Kafka, RDBMS systems & Object Stores with ease Java/Spark-based data processing capabilities. Event-based processing Multi-model storage Multiple language/framework support (Java/.Net/Rest/Spark/BI Tools/SQL) for data consumption Scalability and Data replication options Data Grid Fault Tolerance Out of the Security and ability to extend the same Multiple Dev-Ops Integration options Support for Hybrid Cloud The features mentioned above qualify it for a centralized Enterprise Data Integration Hub, especially for cases that require time/mission-critical real-time analytics.

It´s a platform out of the box that allows address end to end data use cases, including analytics and real-time data processing (both transactional and analytical)

It's hard to say what do I like the most i guess the social impression