VLDB 2026 Research / reviewers in the wild / expert
Balaji Rathakrishnan
dblp:04/2014
· DBLP profile ↗
2ranked-venue papers
0as first author
0since 2021 · last 2005
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 2
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Databases, data mining, and information retrieval
2 papers |
Data integration and cleaning · 31% Distributed and cloud data management · 24% Query processing and optimization · 24% |
Topics — the 5 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Query processing and optimization › query optimization
cost-based optimization |
0.1 | 1 | 2005 | Distributed/Heterogeneous Query Processing in Microsoft SQL Server · ICDE 2005 |
Distributed and cloud data management
distributed query processing |
0.1 | 1 | 2005 | Distributed/Heterogeneous Query Processing in Microsoft SQL Server · ICDE 2005 |
Data integration and cleaning
heterogeneous query processing |
0.1 | 1 | 2005 | Distributed/Heterogeneous Query Processing in Microsoft SQL Server · ICDE 2005 |
Database system architecture and tuning
extensibility |
0.0 | 1 | 2004 | Hosting the .NET Runtime in Microsoft SQL Server · SIGMOD Conference 2004 |
Data integration and cleaning
data source integration |
0.0 | 1 | 2005 | Distributed/Heterogeneous Query Processing in Microsoft SQL Server · ICDE 2005 |
Methods — techniques the papers use, named apart from their topics
algebraic transformations · 0.1OLE DB interfaces · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | Distributed/Heterogeneous Query Processing in Microsoft SQL ServerabstractThis 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. José A. Blakeley, Conor Cunningham, Nigel Ellis, Balaji Rathakrishnan, Ming-Chuan Wu |
ICDE | 4 |
| 2004 | Hosting the .NET Runtime in Microsoft SQL ServerabstractThe 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. Alazel Acheson, Mason Bendixen, José A. Blakeley, Peter Carlin, Ebru Ersan, Xiaowei Jiang, Christian Kleinerman, Balaji Rathakrishnan, Gideon Schaller, Beysim Sezgin, Ramachandran Venkatesh |
SIGMOD Conference | 9 |