McGraw-Hill authors represent the leading experts in their fields and are dedicated to improving the lives, careers, and interests of readers worldwide McGraw-Hill authors represent the leading experts in their fields and are dedicated to improving the lives, careers, and interests of readers worldwide

• IntroductionChapter 1: All Aboard! 15-Minute DB2 10.5 Tour Starts HereWhat Was Delivered: A Recap of DB2 10.1DB2 10.1 Delivered Performance ImprovementsDB2 10.1 Delivered Even Lower Storage CostsDB2 10.1 Delivered Improved Availability and ScalabilityDB2 10.1 Delivered More Security for MultitenancyDB2 10.1 Delivered the Dawn of DB2 NoSQL SupportDB2 10.1 Delivered Even More Oracle CompatibilityDB2 10.1 Delivered Temporal Data ManagementIntroducing DB2 10.5: The Short TourDB2 with BLU AccelerationA Final Thought Before You Delve into the Wild BLU YonderDB2 pureScale Goes Ultra HA, DR, and More…DB2 as a JavaScript Object Notation Document StoreOracle CompatibilityTools, Tools, ToolsWrapping It Up…Chapter 2: DB2 pureScale Reaches Even HigherIn Case It’s Your First Time… Recapping DB2 pureScaleYou Can Put DB2 pureScale in More PlacesDB2 pureScale Gets Even More AvailableDB2 pureScale Gets High Availability Disaster RecoveryKeep on Rolling, Rolling, Rolling: DB2 Fix Pack Updates Go OnlineAdding Members OnlineCross-Topology Backup and RestoreWorkload Consolidation in a DB2 pureScale EnvironmentExplicit Hierarchical LockingWrapping It Up…Chapter 3: BLU Acceleration: Next-Generation Analytics Technology Will Leave Others “BLU” with EnvyWhat Is BLU Acceleration?Next-Generation Database for AnalyticsSeamlessly IntegratedHardware OptimizedConvince Me to Take BLU Acceleration for a Test DrivePedal to the Floor: How Fast Is BLU Acceleration?From Minimized to Minuscule: BLU Acceleration Compression RatiosWhere Will I Use BLU Acceleration?How BLU Acceleration Came to Be: The Seven Big IdeasBig Idea Number 1: KISS ItBig Idea Number 2: Actionable Compression and Computer-Friendly EncodingBig Idea Number 3: Multiplying the Power of the CPUBig Idea Number 4: Parallel Vector ProcessingBig Idea Number 5: Get Organized…by ColumnBig Idea Number 6: Dynamic In-Memory ProcessingBig Idea Number 7: Data SkippingSeven Big Ideas Optimize the Hardware StackWhen Seven Big Ideas Deliver One Incredible OpportunityUnder the Hood: A Quick Peek Behind the Scenes of BLU AccelerationBLU Acceleration Is a New Format for the Bytes in a Table, NOT a New Database EngineThe Day In and Day Out of BLU AccelerationInformational Constraints, Uniqueness, and BLU AccelerationGetting the Data to BLU: Ingestion in a BLU Acceleration EnvironmentAutomated Workload Management That Is BLU-AwareQuerying Column-Organized and Row-Organized TablesThe Maintenance-Free Life of a BLU Acceleration TableGetting to BLU-Accelerated TablesReady, Set, Go! Hints and Tips We Learned Along the WayFirst Things First: Do This!Automated Memory TuningFor Optimal Compression Results…Data Statistics? Don’t Bother, We’ve Got It CoveredINSERT PerformanceHow to Skip More: Get the Most Out of Data SkippingA NextGen Database Does Best with the Latest HardwareMemory, Memory, and More MemoryConverting Your Row-Organized Tables into Column-Organized TablesWrapping It Up…Chapter 4: Miscellaneous Performance and SQL Compatibility EnhancementsExpression-Based IndexesGet Faster: Query Processing Before and After DB2 10.5 with Support for Index ExpressionsExpression-Based Indexes Make Application Development EasierExcluding NULL Keys from IndexesIndex NULL Exclusion Simplifies Application DevelopmentWhen 2 + 2 = 4: Getting Even Richer Semantics by Combining FeaturesRandom Ordering for Index ColumnsTo Random Order an Index Column or Not to Random Order an Index Column…That Is the QuestionMore Data on a Row: Extended Row SizeChapter 5: Miscellaneous Availability EnhancementsBetter Online Space Reclamation for Insert Time Clustering TablesUnderstanding Insert Time Clustering Tables—A PrimerWhat’s New for Insert Time Clustered Tables in DB2 10.5Other DB2 10.5 Reorganization EnhancementsFastpath! Collapsing Overflow and Pointer RecordsSupport for Adaptive Compression with Online, In-place ReorganizationSupport for ADMIN_MOVE_TABLE Routine with Referential ConstraintsWrapping It Up…Chapter 6: DB2 10.5: New Era ApplicationsWhat’s in the NoSQL Name?DB2 pureXML: Where DB2 First Dipped Its “Toe” in the NoSQL PoolDB2 as a Graph Database: RDF, SPARQL, and Other Shiny ThingsDB2 as a JSON Document StoreWhat Does JSON Look Like? JSON Document StructureFrequent Application ChangesFlexible Data InterchangeDocument Store DatabasesManipulating JSON Documents with DB2Wrapping It Up…

McGraw-Hill authors represent the leading experts in their fields and are dedicated to improving the lives, careers, and interests of readers worldwide McGraw-Hill authors represent the leading experts in their fields and are dedicated to improving the lives, careers, and interests of readers worldwide

• IntroductionChapter 1: All Aboard! 15-Minute DB2 10.5 Tour Starts HereWhat Was Delivered: A Recap of DB2 10.1DB2 10.1 Delivered Performance ImprovementsDB2 10.1 Delivered Even Lower Storage CostsDB2 10.1 Delivered Improved Availability and ScalabilityDB2 10.1 Delivered More Security for MultitenancyDB2 10.1 Delivered the Dawn of DB2 NoSQL SupportDB2 10.1 Delivered Even More Oracle CompatibilityDB2 10.1 Delivered Temporal Data ManagementIntroducing DB2 10.5: The Short TourDB2 with BLU AccelerationA Final Thought Before You Delve into the Wild BLU YonderDB2 pureScale Goes Ultra HA, DR, and More…DB2 as a JavaScript Object Notation Document StoreOracle CompatibilityTools, Tools, ToolsWrapping It Up…Chapter 2: DB2 pureScale Reaches Even HigherIn Case It’s Your First Time… Recapping DB2 pureScaleYou Can Put DB2 pureScale in More PlacesDB2 pureScale Gets Even More AvailableDB2 pureScale Gets High Availability Disaster RecoveryKeep on Rolling, Rolling, Rolling: DB2 Fix Pack Updates Go OnlineAdding Members OnlineCross-Topology Backup and RestoreWorkload Consolidation in a DB2 pureScale EnvironmentExplicit Hierarchical LockingWrapping It Up…Chapter 3: BLU Acceleration: Next-Generation Analytics Technology Will Leave Others “BLU” with EnvyWhat Is BLU Acceleration?Next-Generation Database for AnalyticsSeamlessly IntegratedHardware OptimizedConvince Me to Take BLU Acceleration for a Test DrivePedal to the Floor: How Fast Is BLU Acceleration?From Minimized to Minuscule: BLU Acceleration Compression RatiosWhere Will I Use BLU Acceleration?How BLU Acceleration Came to Be: The Seven Big IdeasBig Idea Number 1: KISS ItBig Idea Number 2: Actionable Compression and Computer-Friendly EncodingBig Idea Number 3: Multiplying the Power of the CPUBig Idea Number 4: Parallel Vector ProcessingBig Idea Number 5: Get Organized…by ColumnBig Idea Number 6: Dynamic In-Memory ProcessingBig Idea Number 7: Data SkippingSeven Big Ideas Optimize the Hardware StackWhen Seven Big Ideas Deliver One Incredible OpportunityUnder the Hood: A Quick Peek Behind the Scenes of BLU AccelerationBLU Acceleration Is a New Format for the Bytes in a Table, NOT a New Database EngineThe Day In and Day Out of BLU AccelerationInformational Constraints, Uniqueness, and BLU AccelerationGetting the Data to BLU: Ingestion in a BLU Acceleration EnvironmentAutomated Workload Management That Is BLU-AwareQuerying Column-Organized and Row-Organized TablesThe Maintenance-Free Life of a BLU Acceleration TableGetting to BLU-Accelerated TablesReady, Set, Go! Hints and Tips We Learned Along the WayFirst Things First: Do This!Automated Memory TuningFor Optimal Compression Results…Data Statistics? Don’t Bother, We’ve Got It CoveredINSERT PerformanceHow to Skip More: Get the Most Out of Data SkippingA NextGen Database Does Best with the Latest HardwareMemory, Memory, and More MemoryConverting Your Row-Organized Tables into Column-Organized TablesWrapping It Up…Chapter 4: Miscellaneous Performance and SQL Compatibility EnhancementsExpression-Based IndexesGet Faster: Query Processing Before and After DB2 10.5 with Support for Index ExpressionsExpression-Based Indexes Make Application Development EasierExcluding NULL Keys from IndexesIndex NULL Exclusion Simplifies Application DevelopmentWhen 2 + 2 = 4: Getting Even Richer Semantics by Combining FeaturesRandom Ordering for Index ColumnsTo Random Order an Index Column or Not to Random Order an Index Column…That Is the QuestionMore Data on a Row: Extended Row SizeChapter 5: Miscellaneous Availability EnhancementsBetter Online Space Reclamation for Insert Time Clustering TablesUnderstanding Insert Time Clustering Tables—A PrimerWhat’s New for Insert Time Clustered Tables in DB2 10.5Other DB2 10.5 Reorganization EnhancementsFastpath! Collapsing Overflow and Pointer RecordsSupport for Adaptive Compression with Online, In-place ReorganizationSupport for ADMIN_MOVE_TABLE Routine with Referential ConstraintsWrapping It Up…Chapter 6: DB2 10.5: New Era ApplicationsWhat’s in the NoSQL Name?DB2 pureXML: Where DB2 First Dipped Its “Toe” in the NoSQL PoolDB2 as a Graph Database: RDF, SPARQL, and Other Shiny ThingsDB2 as a JSON Document StoreWhat Does JSON Look Like? JSON Document StructureFrequent Application ChangesFlexible Data InterchangeDocument Store DatabasesManipulating JSON Documents with DB2Wrapping It Up…