Highly scaled out relational database as a service

Highly scaled out relational database as a service Browser SQL Azure Database (Windows Azure Compute) SOAP/REST HTTP/S • Highly scaled Database “as a Service” – beyond hosting (ASP. NET) Windows Azure Compute SQL Azure Database • SQL Server technology foundation • Highly symmetrical Astoria/REST - EDM HTTP/S App Code T-SQL (TDS) Relational database service SQL Server Reporting Server (on-premises) T-SQL (TDS) MS Datacenter - AD Federation (Live. Id /. Net Svcs ACS) Customer Value Props ü Self-provisioning and capacity on demand ü Symmetry w/ on-premises database platform ü Automatic high-availability and fault-tolerance ü Automated DB maintenance (infrastructure) ü Simple, flexible pricing – “pay as you grow”

Database and workload partitioning is a classic technique for harnessing the power of many computers to achieve: • Better price/performance • Levels of throughput not possible with a single machine Classic scale-out challenges addressed by SQL Azure: ü ü ü Highly available service on top of commodity hardware Zero administration cost of cluster HW, OS and SW Access to elastic pool of resources Pay as you grow No-friction provisioning of databases Create databases without ever running out of HW

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Client Applications Azure Roles . Net Service Bus Dynamic Worker (tasks uploaded as blobs) http: // Ticket. Direct. * Azure Storage Blobs to store web and worker role resources ------- Distributed Cache Worker Mem. Cache Tables to record server & partition information Partitioner Worker WCF Queues for communication between clients and roles Castellan. Azure • Box Office sales • Ticket Printing • System Administration • Venue/Event Management • Partitioning On Premise SQL Server Castellan Venue SQL Azure Castellan Venue DB 1 Partition(s) DB’s Castellan Venue DB 2 Partition(s) DB’s Castellan Venue DBN Partition(s) DB’s One application DB, many venue DB’s – each partitioned in to many parts (40+) . . . Castellan. old (VB 6)

High Storage and Transactional throughput Transactional Requirements • • Single Database No Partitioning Low • • Partitioned Data Partitioning based on Application Requirements (IOPS) Low Storage Requirements Partitioned Data Partitioning based on Application Requirements (IOPS, Storage or both) • • Partitioned Data Partitioning Based on Application Requirements (Storage) High

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>>FUTURE Better tooling for developers and administrators: o Dynamic database partition splits o Ability to merge database partitions o Improved schema management across database partitions Database Features for scale-out application patterns: o Connection management o Fan-out query support

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