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Real-Time & Stream Data Management Push-Based Data in Research & Practice

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 behav...

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Bibliographic Details
Main Authors: Wingerath, Wolfram, Ritter, Norbert (Author), Gessert, Felix (Author)
Format: eBook
Language:English
Published: Cham Springer International Publishing 2019, 2019
Edition:1st ed. 2019
Series:SpringerBriefs in Computer Science
Subjects:
Information Storage And Retrieval
Database Management
Data Structures (computer Science)
Data Structures
Online Access:
Collection: Springer eBooks 2005- - Collection details see MPG.ReNa
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520 |a 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 provides an overview over the different (push-based) 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 real-time databases. It sfirst includes 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, it helps readers build a mental model of the available options 

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