Real-Time & Stream Data Management: Push-Based Data in Research & Practice (SpringerBriefs in Computer Science)
暫譯: 即時與串流數據管理：研究與實踐中的推送數據（計算機科學春季簡報）

While traditional databases excel at complex queries over historical data, they are inherently pull-based and therefore ill-equipped to push new information to clients. Systems for data stream management and processing, on the other hand, are natively push­oriented and thus facilitate reactive behavior. However, they do not retain data indefinitely and are therefore not able to answer historical queries. 

The book will first provide an overview over the different (push-based) mechanisms for data retrieval in each system class and the semantic differences between them. It will also provide a comprehensive overview over the current state of the art in real-time databases. 

It will first include an in-depth system survey of today's real-time databases: Firebase, Meteor, RethinkDB, Parse, Baqend, and others. Second, the high-level classification scheme illustrated above provides a gentle introduction into the system space of data management: Abstracting from the extreme system diversity in this field,