Abstract—An efficient multiversion access structure for a transaction-time database is presented. Our method requires optimal storage and query times for several important queries and logarithmic update times. Three version operations}inserts, updates, and deletes}are allowed on the current database, while queries are allowed on any version, present or past. The following query operations are performed in optimal query time: key range search, key history search, and time range view. The key-range query retrieves all records having keys in a specified key range at a specified time; the key history query retrieves all records with a given key in a specified time range; and the time range view query retrieves all records that were current during a specified time interval. Special cases of these queries include the key search query, which retrieves a particular version of a record, and the snapshot query which reconstructs the database at some past time. To the best of our knowledge no previous multiversion access structure simultaneously supports all these query and version operations within these time and space bounds. The bounds on query operations are worst case per operation, while those for storage space and version operations are (worst-case) amortized over a sequence of version operations. Simulation results show that good storage utilization and query performance is obtained. Index Terms—Transaction-time database, multidimensional data, access methods, data structures, indexing, I/O complexity.

Real-world objects are inherently spatially and temporally referenced, and many database applications rely on databases that record the past, present, and anticipated future locations of, e.g., people or land parcels. As a result, indices that efficiently support queries on the spatio-temporal extents of objects are needed. In contrast, past indexing research has progressed in largely separate spatial and temporal streams. In the former, focus has been on one-, two-, or three-dimensional space; and in the latter, focus has been on one or both of the temporal aspects, or dimensions, of data known as transaction time and valid time. Adding time dimensions to spatial indices, as if time was a spatial dimension, neither supports nor exploits the special properties of time. On the other hand, temporal indices are generally not amenable to extension with spatial dimensions. This paper proposes an efficient and versatile technique for the indexing of spatio-temporal data with discre...

This paper presents the object management facilities being designed into a next-generation data manager, POSTGRES. This system is unique in that it does not invent a new data model for support of objects but chooses instead to extend the relational model with a powerful abstract data typing capability and procedures as full-fledged data base objects. The reasons to remain with the relational model are indicated in this paper along with the POSTGRES relational extensions. 1.

A model for a historical database is described which is based upon time-stamped tuples as the unit of storage. The model includes both physical and logical time-stamps. The techni-cal characteristics of write-once laser discs prevent the use of double logical time-stamps. The model distinguishes version from correction-updates. It is shown that if set-valued attributes are involved the use of null values is unavoidable if back-dated correction-updates are allowed. A method of handling user-defined integrity constraint rules is outlined which involves the mainte-nance of a time-stamped trace of such rules.

this paper we provide an extensive survey of the R-tree evolution, studying the applicability of the structure and its variations to e#cient query processing, accurate proposed cost models, and implementation issues like concurrency control and parallelism. Based on the observation that `space is everywhere', we anticipate that we are in the beginning of the era of the `ubiquitous R-tree' in an analogous manner as B-trees were considered 25 years ago

Conceptual data modeling for complex applications, such as multimedia and spatiotemporal applications, often results in large, complicated and difficult-to-comprehend diagrams. One reason for this is that these diagrams frequently involve repetition of autonomous, semantically meaningful parts that capture similar situations and characteristics. By recognizing such parts and treating them as units, it is possible to simplify the diagrams, as well as the conceptual modeling process. We propose to capture autonomous and semantically meaningful excerpts of diagrams that occur frequently as modeling patterns. Specifically, the paper concerns modeling patterns for conceptual design of spatiotemporal databases. Based on requirements drawn from real applications, it presents a set of modeling patterns that capture spatial, temporal, and spatiotemporal aspects. To facilitate the conceptual design process, these patterns are abbreviated by corresponding spatial, temporal, and spatiotemporal pattern abstractions, termed components. The result is more elegant and less-detailed diagrams that are easier to comprehend, but yet semantically rich. The Entity-Relationship model serves as the context for this study. An extensive example from a real cadastral application illustrates the benefits of using a component-based conceptual model.

A data warehouse provides strong capabilities for answering complex decision support queries. In particular, it is often desirable to query relations as they existed at some point in the past. Much of the research in temporal databases, materialized views, and snapshot databases has some bearing on this concept. In particular, differential files provide a means for storing past versions of relations while conserving storage space. Queries involving these differential files can be optimized in a variety of ways. 1 Introduction Data warehouses are designed to help create and answer complex queries by organizing varied and potentially distributed data in a common environment. Most of the time, the primary source of the data is not the warehouse itself. Instead, the primary source is some sort of legacy transactional system. These legacy systems may not lend themselves well to complex queries. One of the main difficulties in using transactional systems for decision support is that the dat...

Abstract. Among various models like TSQL2, XML and SQL:2003 for temporal databases, TSQL2 is perhaps the most comprehensive one and introduces new constructs for temporal query support. However, these constructs mask the user from the underlying conceptual model and essentially provides a “black box ” flavour. Further, the temporal attributes are not directly accessible. In this paper, we propose a “chronon ” based conceptual (relational) model, which works on a tuple timestamping paradigm. Here, the time attribute is treated in similar fashion as any other attribute and is available to the user for inclusion in SQL statements, making the model easy to understand and use. A corresponding efficient physical model based on the attribute versioning format akin to XML/SQL:2003 has also been proposed and the mapping between the proposed conceptual and physical models has been described. We evaluate the model by comparing with TSQL2 and SQL:2003, and show its equivalence to Allen’s algebra.

: This paper proposes an object-oriented data model which integrates structural and temporal aspects for different kinds of (multimedia) data. These data include traditional atomic types as integers, reals, or character strings together with programs, textual, visual and audio information as they appear in several new application fields (e.g. CAD/CAM, geographical and medical databases). We claim that object oriented database systems have to be extended in order to provide powerful capabilities for modeling, storing and retrieving multimedia data which have not only particular complex structure but also specific temporal constraints. In this paper we propose to integrate structural operators (e.g. tuple, list, set) and temporal relationships (e.g. before, after, equal) for multimedia databases. Temporal aspects are modeled through the notion of Temporal Shadow which incorporates free or bound durations and/or delays. Our model, called STORM, provides sequential and parallel operators ...

Conceptual data modeling for complex applications, such as multimedia and spatiotemporal applications, often results in large, complicated and difficult-to-comprehend diagrams. One reason for this is that these diagrams frequently involve repetition of autonomous, semantically meaningful parts that capture similar situations and characteristics. By recognizing such parts and treating them as units, it is possible to simplify the diagrams, as well as the conceptual modeling process. We propose to capture autonomous and semantically meaningful excerpts of diagrams that occur frequently as modeling patterns. Specifically, the paper concerns modeling patterns for conceptual design of spatiotemporal databases. Based on requirements drawn from real applications, it presents a set of modeling patterns that capture spatial, temporal, and spatiotemporal aspects. To facilitate the conceptual design process, these patterns are abbreviated by corresponding spatial, temporal, and spatiotemporal pattern abstractions, termed components. The result is more elegant and less-detailed diagrams that are easier to comprehend, but yet semantically rich. The Entity-Relationship model serves as the context for this study. An extensive example from a real cadastral application illustrates the benefits of using a component-based conceptual model.