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Springer International Publishing
Real-Time & Stream Data Management: Push-Based Data in Research & Practice
Real-Time & Stream Data Management: Push-Based Data in Research & Practice
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While traditional databases excel at complex queries over historical data, they are inherently pullbased and therefore illequipped 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 provides an overview over the different (pushbased) mechanisms for data retrieval in each system class and the semantic differences between them. It also provides a comprehensive overview over the current state of the art in realtime databases.
It sfirst includes an indepth system survey of today's realtime databases: Firebase, Meteor, RethinkDB, Parse, Baqend, and others. Second, the highlevel classification scheme illustrated above provides a gentle introduction into the system space of data management: Abstracting from the extreme system diversity in this field, it helps readers build a mental model of the available options.
The book provides an overview over the different (pushbased) mechanisms for data retrieval in each system class and the semantic differences between them. It also provides a comprehensive overview over the current state of the art in realtime databases.
It sfirst includes an indepth system survey of today's realtime databases: Firebase, Meteor, RethinkDB, Parse, Baqend, and others. Second, the highlevel classification scheme illustrated above provides a gentle introduction into the system space of data management: Abstracting from the extreme system diversity in this field, it helps readers build a mental model of the available options.
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