SQL is five decades old and has outlasted many programming and query languages that have come and gone during its lifetime. It was born shortly after the introduction of the relational model, and was designed for querying a flat and typed tabular world. Support for modern, flexible data in the SQL standard and in relational database systems has largely been approached via the addition of new column types (e.g. XML or JSON) together with functions to operate on them. It is time for a cleaner solution that retains the benefits that have allowed SQL to be so successful for so long. We describe SQL++, a SQL extension that relaxes SQL's strictness in terms of both object structure (flat → nested) and schema (mandatory → optional), along with a multi-party effort to agree on a core definition and syntax supportable by multiple vendors. SQL++ sees relational data as a subset of a more flexible object model and it sees collections of document data (e.g., JSON) as a natural and supportable relaxation as opposed to a “bolt on” addition via a SQL column type. We describe the core features of SQL++ and explain how its definition can accommodate flexible data, while staying true to SQL in situations where the target data is tabular and strongly typed. Index Terms-semistructured data, query, JSON, SQL, NoSQL

XQuery is a query language under development by the W3C XML Query Working Group. The language contains constructs for navigating, searching, and restructuring XML data. With XML gaining importance as the standard for representing business data, XQuery must support the types of queries that are common in business analytics. One such class of queries is OLAP-style aggregation queries. Although these queries are expressible in XQuery Version 1, the lack of explicit grouping constructs makes the construction of these queries non-intuitive and places a burden on the XQuery engine to recognize and optimize the implicit grouping constructs. Furthermore, although the flexibility of the XML data model provides an opportunity for advanced forms of grouping that are not easily represented in relational systems, these queries are difficult to express using the current XQuery syntax. In this paper, we provide a proposal for extending the XQuery FLWOR expression with explicit syntax for grouping and for numbering of results. We show that these new XQuery constructs not only simplify the construction and evaluation of queries requiring grouping and ranking but also enable complex analytic queries such as moving-window aggregation and rollups along dynamic hierarchies to be expressed without additional language extensions.

As XML has evolved from a document markup language to a widely-used format for exchange of structured and semistructured data, managing large amounts of XML data has become increasingly important. A number of companies, including both established database vendors and startups, have recently announced new XML database systems or new XML functionality integrated into existing database systems. This tutorial will provide an insight into how XML functionality fits into relational database management systems as seen by three major relational vendors: IBM, Microsoft and Oracle.

XQuery is the XML query language currently under development in the World Wide Web Consortium (W3C). XQuery specifications have been published in a series of W3C working drafts, and several reference implementations of the language are already available on the Web. If successful, XQuery has the potential to be one of the most important new computer languages to be introduced in several years. This tutorial will provide an overview of the syntax and semantics of XQuery, as well as insight into the principles that guided the design of the language.

XML data is different from data found in relational databases in several important respects. The article discusses these differences and why they justify development of a new query language for XML. It also reports on the activities of the W3C working group on XML queries.

In this presentation, we will describe a collection of new object-relational features that have been added to IBM's DB2 Universal Database (UDB) system. The features to be described include support for structured types, object references, and hierarchies of typed tables and views. These features will be covered from the perspective of a database designer or end user. In addition to presenting the features presently available in DB2 UDB V5.2, which became available in Fall 1998, we will discuss the expected evolution and impact of this technology over time.

Polyglot is an extensible relational-database-type system that supports inheritance, encapsulation, and dynamic method dispatch. It allows use from multiple application languages and permits objects to retain their behavior as they cross the boundary between database and application program. The authors describe the design of Polyglot, extensions to the structured query language (SQL) to support the use of Polyglot types and methods, and the implementation of Polyglot in the Starburst relational database system.>

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.

System R is a database management system which provides a high level relational data interface. The systems provides a high level of data independence by isolating the end user as much as possible from underlying storage structures. The system permits definition of a variety of relational views on common underlying data. Data control features are provided, including authorization, integrity assertions, triggered transactions, a logging and recovery subsystem, and facilities for maintaining data consistency in a shared-update environment. This paper contains a description of the overall architecture and design of the system. At the present time the system is being implemented and the design evaluated. We emphasize that System R is a vehicle for research in database architecture, and is not planned as a product.

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This paper defines an integrity subsystem for an integrated data base management system, and shows how integrity is distinguished from the related areas of security, consistency, and reliability. The integrity subsystem guards the data base against semantic errors by permitting users to make assertions which define the correctness of the data base, and to specify actions to be taken when the assertions are not satisfied. Several categories of assertions are considered, including tuple-vs. set-oriented, state- vs. transition-oriented, immediate vs. delayed, and "hard" vs. "soft" assertions. The related areas of data definition facilities, compatibility of data items, and handling of null values are explored. Facilities are specified by means of which a user may create, drop, or examine integrity assertions.

In a multiprogramming, virtual-memory computing system, many processes compete simultaneously for system resources, which include CPU's, main memory page frames, and the transmission capacity of the paging drum. (We define a “process” here as a program with its own virtual memory, requiring an allocation of real memory and a CPU in order to execute). This paper studies ways of allocating resources to processes in order to maximize throughput in systems which are not CPU-bound.