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The End of the DBMS (as we know it)

The End of the DBMS (as we know it). Vijayshankar Raman Garret Swart IBM Almaden. Disclaimer: We don’t mean anything that we say! Don’t hold it against IBM, or our manager, or our families. The End of the DBMS. Encapsulation is good for programmers; Bad for execution

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The End of the DBMS (as we know it)

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  1. The End of the DBMS(as we know it) Vijayshankar Raman Garret Swart IBM Almaden Disclaimer: We don’t mean anything that we say! Don’t hold it against IBM, or our manager, or our families

  2. The End of the DBMS • Encapsulation is good for programmers; Bad for execution • Currently encapsulation ties software to hardware at design time • Today, where the code runs determines how it is written • Browser => Javascript • Web App => J2EE or .NET • DBMS => Stored procedure or SQL • We propose: • Service Oriented Execution Model for all code • Single programming environment/language • Orchestration Optimizer • Transparently moves code across hardware components • The SOEM replaces all other computer languages • The OO replaces the DBMS as we know it

  3. HTML & Javascript SQL & Stored Proc httpd.conf BPEL4WS Java/C# • Each component has its own language and environment • Logical to Physical mapping of software to hardware should take place AT EXECUTION TIME, unhindered by encapsulation Today, code is tied to a particular programming environment Browser Web Server Workflow Engine App Server DBMS Virtual Storage Server Disk

  4. Service Oriented Execution Model • Everything is a represented as a service: • Each record in a table (getters for attributes) • Each language object • Each storage device • Software == Service Orchestration • A table is a service that represents a set of services • A relational operator is a service, that composes a set of services • A query is a composition of relational operators • A service is a workflow using queries and other service invocations

  5. Orchestration Optimization • Logical  Physical mapping: Subsumes old fashioned • query optimization, • service scheduling • compiler level optimization • Will execute model on appropriate hardware • Disregarding encapsulation • Accounting for security and performance • E.g. • Data reduction can run in storage • Data aggregation could run in client • Rendering could run on app server • Change from service invocation to function call to inline method

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