The Garlic project

• Authors: M. Tork Roth;M. Arya;L. Haas;M. Carey;W. Cody;R. Fagin;P. Schwarz;J. Thomas;E. Wimmers
• Venue: SIGMOD '96 Proceedings of the 1996 ACM SIGMOD international conference on Management of data
• Year: 1996

The goal of the Garlic [1] project is to build a multimedia information system capable of integrating data that resides in different database systems as well as in a variety of non-database data servers. This integration must be enabled while maintaining the independence of the data servers, and without creating copies of their data. "Multimedia" should be interpreted broadly to mean not only images, video, and audio, but also text and application specific data types (e.g., CAD drawings, medical objects, …). Since much of this data is naturally modeled by objects, Garlic provides an object-oriented schema to applications, interprets object queries, creates execution plans for sending pieces of queries to the appropriate data servers, and assembles query results for delivery back to the applications. A significant focus of the project is support for "intelligent" data servers, i.e., servers that provide media-specific indexing and query capabilities [2]. Database optimization technology is being extended to deal with heterogeneous collections of data servers so that efficient data access plans can be employed for multi-repository queries.A prototype of the Garlic system has been operational since January 1995. Queries are expressed in an SQL-like query language that has been extended to include object-oriented features such as reference-valued attributes and nested sets. In addition to a C++ API, Garlic supports a novel query/browser interface called PESTO [3]. This component of Garlic provides end users of the system with a friendly, graphical interface that supports interactive browsing, navigation, and querying of the contents of Garlic databases. Unlike existing interfaces to databases, PESTO allows users to move back and forth seamlessly between querying and browsing activities, using queries to identify interesting subsets of the database, browsing the subset, querying the content of a set-valued attribute of a particularly interesting object in the subset, and so on.