In this paper, we present the ArchIS system that achieves full-functionality transaction-time databases without requiring temporal extensions in XML or database standards. ArchIS’ architecture uses (a) XML to support temporally grouped (virtual) representations of the database history, (b) XQuery to express powerful temporal queries on such views, (c) temporal clustering and indexing techniques for managing the actual historical data in a relational database, and (d) SQL/XML for executing the queries on the XML views as equivalent queries on the relational database. The performance studies presented in the paper show that ArchIS is quite effective at storing and retrieving under complex query conditions the transaction-time history of relational databases.

Relational data streams and XML streams have previously provided two separate research foci, but their unified support by a single Data Stream Management System (DSMS) is very desirable from an application viewpoint. In this paper, we propose a simple approach to extend relational DSMSs to support both kinds of streams efficiently. In our Stream Mill system, XML streams expressed as SAX events, can be easily transformed into relational streams, and vice versa. This enables a close cooperation of their query languages, resulting in great power and flexibility. For instance, XQuery can call functions defined in our SQLbased Expressive Stream Language (ESL) using the logical/ physical windows that have proved so useful on relational data streams. Many benefits are also gained at the system level, since relational DSMS techniques for load shedding, memory management, query scheduling, approximate query answering, and synopsis maintenance can now be applied to XML streams. Moreover, the many FSA-based optimization techniques developed for XPath and XQuery can be easily and efficiently incorporated in our system. Indeed, we show that YFilter, which is capable of efficiently processing multiple complex XML queries, can be easily integrated in Stream Mill via ESL user-defined and systemdefined aggregates. This approach produces a powerful and flexible system where relational and XML streams are unified and processed efficiently.

While the introduction of temporal extensions into database standards has proven difficult to achieve, the newly introduced SQL:2003 and XML/XQuery standards have actually enhanced our ability to support temporal applications in commercial database systems. We illustrate this point by discussing three approaches that use temporally grouped representations. We first compare the approaches at the logical level using a common set of queries; then we turn to the physical level and discuss our ArchIS system that supports the three different approaches efficiently in one unified physical implementation. We conclude that the approaches of managing transaction-time information using XML and SQL can be integrated and supported efficiently within the current standards, and claim that the proposed approach can be extended to valid-time and bitemporal databases.

Historical information can be effectively preserved using XML and searched through powerful historical queries written in XQuery. Indeed, by storing the successive versions of a document in an incremental fashion, XML repositories and data warehouses can achieve (i) the efficient preservation of critical information, (ii) its representation using a temporally grouped data model and (iii) the ability of supporting historical queries on the evolution of documents and their contents using XQuery. The proposed approach can be applied uniformly to (a) XML document archives and (b) transaction time databases published in XML and queried in XQuery. Our case studies include the UCLA course catalog, W3C Xlink standards, and the CIA WorldFact Book, besides relational databases. The experience described here and in the work of Wang et al. (2005 and 2003) suggests that current standards provide reasonable support for temporal applications at the logical level, whereas many challenges remain at the physical level.