Summary form only given. For the past three decades, those of us in the database field have principally focused attention and significant effort on technology for storing, querying, accessing, and securing data with well-known structure in high-performance data management systems. Our focus has been riveted on performance, performance, and performance. The world has changed dramatically since the early days of database management systems, however. The dynamics of DBMS have changed, moving from supporting back office systems, to front offices, to Web-based systems. Computer architecture has changed, as we have moved from systems where 256 K was a large size memory, disk drives were very expensive, most processors were water-cooled, and screens glowed with green characters. Not only has more data been produced in the last several years than in all previous history, but also more and more of it is in digital form. Accelerated pace and higher expectations driven by competitive necessity have changed the nature of database solutions from well-understood batch-oriented processing to real-time, ad hoc query on continuously streaming data. All these changes are coming together to create a new set of challenges for the decade ahead. The author discusses the top five of these challenges in the database area.

This paper describes a personal perspective of the kinds of contributions that systems research and theoretical research make to one another particularly in the database area. Examples of each kind of contribution are given, and then several case studies from the author a personal experience are presented. The case studies illustrate database systems research where theoretical work contributed to systems results and vice versa. Areas of database systems which need more contributions from the theoretical community will also be presented.

The design and implementation of R*, an experimental prototype of a distributed system for the management of interrelated, voluntarily cooperating, but also autonomous databases is based on several major objectives: site autonomy, transparency, ease of use and performance. This paper discusses the way data definition and control statements are executed in a distributed environment and shows how the general objectives are fulfilled. Specialized distributed execution facilities have been developed to facilitate the implementation of complex multi-site functions. This paper describes the facilities and methodology used to implement the distributed processing needed to perform multi-site data definition operations in R*.

System R supports a high-level relational user language called SQL which may be used by ad hoc users at terminals or as an embedded data sublanguage in PL/I or COBOL. Host-language programs with embedded SQL statements are processed by the System R precompiler which replaces the SQL statements by calls to a machine-language access module. The precompilation approach removes much of the work of parsing, name binding, and access path selection from the path of a running program, enabling highly efficient support for repetitive transactions. Ad hoc queries are processed by a similar approach of name binding and access path selection which takes place on-line when the query is specified. By providing a flexible spectrum of binding times, System R permits transaction-oriented programs and ad hoc query users to share a database without loss of efficiency. System R is an experimental database management system designed and built by members of the IBM San Jose Research Laboratory as part of a research program on the relational model of data. This paper describes the architecture of System R, and gives some preliminary measurements of system performance in both the ad hoc query and the “canned program” environments.

In a high level query and data manipulation language such as SQL, requests are stated non-procedurally, without reference to access paths. This paper describes how System R chooses access paths for both simple (single relation) and complex queries (such as joins), given a user specification of desired data as a boolean expression of predicates. System R is an experimental database management system developed to carry out research on the relational model of data. System R was designed and built by members of the IBM San Jose Research Laboratory.