| 000 | 03094nam a22005055i 4500 | ||
|---|---|---|---|
| 001 | 978-3-030-10555-6 | ||
| 003 | DE-He213 | ||
| 005 | 20200812102319.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 190102s2019 gw | s |||| 0|eng d | ||
| 020 |
_a9783030105556 _9978-3-030-10555-6 |
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| 024 | 7 |
_a10.1007/978-3-030-10555-6 _2doi |
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| 040 | _cCUS | ||
| 050 | 4 | _aQA75.5-76.95 | |
| 072 | 7 |
_aUNH _2bicssc |
|
| 072 | 7 |
_aCOM030000 _2bisacsh |
|
| 072 | 7 |
_aUNH _2thema |
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| 072 | 7 |
_aUND _2thema |
|
| 082 | 0 | 4 |
_a025.04 _223 |
| 100 | 1 |
_aWingerath, Wolfram. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut |
|
| 245 | 1 | 0 |
_aReal-Time & Stream Data Management _h[electronic resource] : _bPush-Based Data in Research & Practice / _cby Wolfram Wingerath, Norbert Ritter, Felix Gessert. |
| 250 | _a1st ed. 2019. | ||
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2019. |
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| 300 |
_aIX, 77 p. 15 illus., 6 illus. in color. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
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| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
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| 490 | 1 |
_aSpringerBriefs in Computer Science, _x2191-5768 |
|
| 520 | _aWhile 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 pushÂoriented 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. | ||
| 650 | 0 | _aInformation storage and retrieval. | |
| 650 | 0 | _aDatabase management. | |
| 650 | 0 | _aData structures (Computer science). | |
| 650 | 1 | 4 |
_aInformation Storage and Retrieval. _0https://scigraph.springernature.com/ontologies/product-market-codes/I18032 |
| 650 | 2 | 4 |
_aDatabase Management. _0https://scigraph.springernature.com/ontologies/product-market-codes/I18024 |
| 650 | 2 | 4 |
_aData Structures. _0https://scigraph.springernature.com/ontologies/product-market-codes/I15017 |
| 700 | 1 | _aRitter, Norbert. | |
| 700 | 1 | _aGessert, Felix. | |
| 830 | 0 |
_aSpringerBriefs in Computer Science, _x2191-5768 |
|
| 856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-030-10555-6 |
| 912 | _aZDB-2-SCS | ||
| 912 | _aZDB-2-SXCS | ||
| 942 | _cEBK | ||
| 999 |
_c202598 _d202598 |
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