Balaji Rathakrishnan

Hosting the .NET Runtime in Microsoft SQL server

The integration of the .NET Common Language Runtime (CLR) inside the SQL Server DBMS enables database programmers to write business logic in the form of functions, stored procedures, triggers, data types, and aggregates using modern programming languages such as C#, Visual Basic, C++, COBOL, and J++. This paper presents three main aspects of this work. First, it describes the architecture of the integration of the CLR inside the SQL Server database process to provide a safe, scalable, secure, and efficient environment to run user code. Second, it describes our approach to defining and enforcing extensibility contracts to allow a tight integration of types, aggregates, functions, triggers, and procedures written in modern languages with the DBMS. Finally, it presents initial performance results showing the efficiency of user-defined types and functions relative to equivalent native DBMS features.

Distributed/heterogeneous query processing in Microsoft SQL server

This paper presents an architecture overview of the distributed, heterogeneous query processor (DHQP) in the Microsoft SQL server database system to enable queries over a large collection of diverse data sources. The paper highlights three salient aspects of the architecture. First, the system introduces well-defined abstractions such as connections, commands, and rowsets that enable sources to plug into the system. These abstractions are formalized by the OLE DB data access interfaces. The generality of OLE DB and its broad industry adoption enables our system to reach a very large collection of diverse data sources ranging from personal productivity tools, to database management systems, to file system data. Second, the DHQP is built-in to the relational optimizer and execution engine of the system. This enables DH queries and updates to benefit from the cost-based algebraic transformations and execution strategies available in the system. Finally, the architecture is inherently extensible to support new data sources as they emerge as well as serves as a key extensibility point for the relational engine to add new features such as full-text search and distributed partitioned views.