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010   $a3-319-20711-3
024 7 $a10.1007/978-3-319-20711-7
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035   $a(DE-He213)978-3-319-20711-7
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100   $a20150707d2016      u|         0
101 0 $aeng
135   $aur|n|---|||||
181   $ctxt
182   $cc
183   $acr
200 10$aBuilding a Columnar Database on RAMCloud $eDatabase Design for the Low-Latency Enabled Data Center /$fby Christian Tinnefeld
205   $a1st ed. 2016.
210  1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2016.
215   $a1 online resource (139 p.)
225 1 $aIn-Memory Data Management Research,$x2196-8055
300   $aDescription based upon print version of record.
311   $a3-319-20710-5 
320   $aIncludes bibliographical references.
327   $aPart I: A Database System Architecture for a Shared Main Memory-Based Storage -- Part II: Database Operator Execution on a Shared Main Memory-Based Storage -- Part III: Evaluation -- Part IV: Conclusions.
330   $aThis book examines the field of parallel database management systems and illustrates the great variety of solutions based on a shared-storage or a shared-nothing architecture. Constantly dropping memory prices and the desire to operate with low-latency responses on large sets of data paved the way for main memory-based parallel database management systems. However, this area is currently dominated by the shared-nothing approach in order to preserve the in-memory performance advantage by processing data locally on each server. The main argument this book makes is that such an unilateral development will cease due to the combination of the following three trends: a) Today?s network technology features remote direct memory access (RDMA) and narrows the performance gap between accessing main memory on a server and of a remote server to and even below a single order of magnitude. b) Modern storage systems scale gracefully, are elastic, and provide high-availability. c) A modern storage system such as Stanford?s RAMCloud even keeps all data resident in the main memory. Exploiting these characteristics in the context of a main memory-based parallel database management system is desirable. The book demonstrates that the advent of RDMA-enabled network technology makes the creation of a parallel main memory DBMS based on a shared-storage approach feasible.
410  0$aIn-Memory Data Management Research,$x2196-8055
606   $aManagement information systems
606   $aDatabase management
606   $aComputer memory systems
606   $aData structures (Computer science)
606   $aBusiness IT Infrastructure$3https://scigraph.springernature.com/ontologies/product-market-codes/522040
606   $aDatabase Management$3https://scigraph.springernature.com/ontologies/product-market-codes/I18024
606   $aMemory Structures$3https://scigraph.springernature.com/ontologies/product-market-codes/I12034
606   $aData Storage Representation$3https://scigraph.springernature.com/ontologies/product-market-codes/I15025
615  0$aManagement information systems.
615  0$aDatabase management.
615  0$aComputer memory systems.
615  0$aData structures (Computer science).
615 14$aBusiness IT Infrastructure.
615 24$aDatabase Management.
615 24$aMemory Structures.
615 24$aData Storage Representation.
676   $a005.74
700   $aTinnefeld$b Christian$4aut$4http://id.loc.gov/vocabulary/relators/aut$0963260
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9910254942203321
996   $aBuilding a Columnar Database on RAMCloud$92184073
997   $aUNINA