A temporal database contains time-varying data. In a real-time database transactions have deadlines or timing constraints. In this paper we review the substantial research in these two heretofore separate research areas. We first characterize the time domain, then investigate temporal and real-time data models. We evaluate temporal and real-time query languages along several dimensions. Temporal and real-time DBMS implementation is examined. We conclude with a summary of the major accomplishments of the research to date, and list several research questions that should be addressed next. Keywords: object-oriented database, relational databases, query language, temporal data model, time-constrained database, transaction time, user-defined time, valid time 1 Introduction Time is an important aspect of all real-world phenomena. Events occur at specific points in time; objects and the relationships among objects exist over time. The ability to model this temporal dimension of the real worl...

This paper provides a systematic and comprehensive study of the underlying semantics of temporal databases, summarizing the results of an intensive collaboration between the two authors over the last five years. We first examine how facts may be associated with time, most prominently with one or more dimensions of valid time and transaction time. One common case is that of a bitemporal relation, in which facts are associated with exactly one valid time and one transaction time. These two times may be related in various ways, yielding temporal specialization. Multiple transaction times arise when a fact is stored in one database, then later replicated or transferred to another database. By retaining the transaction times, termed temporal generalization, the original relation can be effectively queried by referencing only the final relation. We attempt to capture the essence of time-varying information via a very simple data model, the bitemporal conceptual data model. Emphasis is placed...

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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...

This paper compares different indexing techniques proposed for supporting efficient access to temporal data. The comparison is based on a collection of important performance criteria, including the space consumed, update processing, and query time for representative queries. The comparison is based on worst-case analysis, hence no assumptions on data distribution or query frequencies are made. When a number of methods have the same asymptotic worst-case behavior, features in the methods that affect average case behavior are discussed. Additional criteria examined are the pagination of an index, the ability to cluster related data together, and the ability to efficiently separate old from current data (so that larger archival storage media such as write-once optical disks can be used). The purpose of the paper is to identify the difficult problems in accessing temporal data and describe how the different methods aim to solve them. A general lower bound for answering basic temporal queries is also introduced.