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The Montage Extensible DataBlade Achitecture.

Michael Ubell: The Montage Extensible DataBlade Achitecture. SIGMOD Conference 1994: 482
@inproceedings{DBLP:conf/sigmod/Ubell94,
  author    = {Michael Ubell},
  editor    = {Richard T. Snodgrass and
               Marianne Winslett},
  title     = {The Montage Extensible DataBlade Achitecture},
  booktitle = {Proceedings of the 1994 ACM SIGMOD International Conference on
               Management of Data, Minneapolis, Minnesota, May 24-27, 1994},
  publisher = {ACM Press},
  year      = {1994},
  pages     = {482},
  ee        = {http://doi.acm.org/10.1145/191839.191939, db/conf/sigmod/Ubell94.html},
  crossref  = {DBLP:conf/sigmod/94},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

Relational database systems have supported business applications for over a decade, providing capabilities such as optimization, concurrency, recovery and data independence. Customers now seek to integrate more areas of their business into a database framework. New applications need data management systems that handle a variety of data types, such as images, drawings, spatial information, time series and documents. These data types must be integrated with traditional data and with each other in a system that provides the same capabilities as relational systems. Relational systems were initially limited to simple data types: numbers, character strings, dates and money. Although relational database vendors have added some new data types, they lack the extensible architecture needed for an integrated solution. Often these extensions appear as wrappers with restricted capabilities and limited integration with other data types.

The Montage database system supports general extensibility of integrated data types. User definable capabilities include base and composite types, C and SQL functions, and functional indices. These features are dynamic: they are added to the system using SQL-3 data definition language. New types of access methods and storage managers are also easily added to the system. The optimizer can use new statistics and formulas to determine when to choose a new access method and the cost of executing a user defined function.

In this architecture the database management system can be thought of as a `razor' into which technology specific `DataBlades' are inserted. DataBlades are packages of data types, functions (or methods) defined on those types, and access methods customized for those types and functions. DataBlades range in specificity and can address technical areas (images), industry sectors (medical) or specific companies (Medical Widgets Corporation). DataBlades may be written by Montage, third parties, or end users.

Montage offers DataBlades for textual document, spatial, image and statistical applications. DataBlades for OCR, time series and isochronous (real-time) data are under development. The latter DataBlade will include a special storage manager to optimize the data delivery. Other vendors can easily add DataBlades that exploit their own expertise.

For example, Montage offers a textual document blade that integrates a third party format conversion suite with a document data type and a full text indexing access method. Queries involving full text search may be combined in relational queries with other data types:

SELECT * FROM employees WHERE
Contains(resume,
'sql or quel and programming')
AND dept = 'Marketing';

The Montage data manager implements SQL-92 with data type and function extensions from SQL3, including type and table hierarchies, multiple inheritance, object identifiers and function overloading. It also implements a general rules and alerters system. Rules may be placed on data retrieval as well as on data modification statements. Alerters can be used to signal other processes when a rule has fired. Dump, restore, rollforward and copy utilities are also provided.

The Montage system runs as a client-server application. Servers are supported in various UNIX environments. Clients may be on UNIX, Windows or Macintosh systems. C-functions registered in the database may either be dynamically linked to the server or be run in the client application during development (debugging) or production (performance, security).

Applications may employ multiple DataBlades. For example an integrated insurance application combines image, document, OCR, spatial, statistical and financial data. By storing all insurance data, Montage encapsulates the knowledge of business practices to a centralized repository where it is automatically applied to all application programs. The true power of the system is in managing all the data, rules and functions for a business in a uniformly accessible, integrated extensible database.

DataBlade is a trademark of Montage Software, Inc.

Copyright © 1994 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.


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Richard T. Snodgrass, Marianne Winslett (Eds.): Proceedings of the 1994 ACM SIGMOD International Conference on Management of Data, Minneapolis, Minnesota, May 24-27, 1994. ACM Press 1994 BibTeX , SIGMOD Record 23(2), June 1994
Contents

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[Index Terms]
[Abstract in PDF Format, 103 KB]

References

[1]
Michael Stonebraker: The Miro DBMS. SIGMOD Conference 1993: 439 BibTeX
[2]
...

Referenced by

  1. Swarup Acharya, Viswanath Poosala, Sridhar Ramaswamy: Selectivity Estimation in Spatial Databases. SIGMOD Conference 1999: 13-24
  2. Aya Soffer, Hanan Samet: Integrating Symbolic Images into a Multimedia Database System Using Classification and Abstraction Approaches. VLDB J. 7(4): 253-274(1998)
  3. Lars Arge, Octavian Procopiuc, Sridhar Ramaswamy, Torsten Suel, Jeffrey Scott Vitter: Scalable Sweeping-Based Spatial Join. VLDB 1998: 570-581
  4. Stéphane Grumbach, Philippe Rigaux, Luc Segoufin: The DEDALE System for Complex Spatial Queries. SIGMOD Conference 1998: 213-224
  5. Yun-Wu Huang, Ning Jing, Elke A. Rundensteiner: A Cost Model for Estimating the Performance of Spatial Joins Using R-trees. SSDBM 1997: 30-38
  6. Chialin Chang, Bongki Moon, Anurag Acharya, Carter Shock, Alan Sussman, Joel H. Saltz: Titan: A High-Performance Remote Sensing Database. ICDE 1997: 375-384
  7. Roberta Cochrane, Hamid Pirahesh, Nelson Mendonça Mattos: Integrating Triggers and Declarative Constraints in SQL Database Sytems. VLDB 1996: 567-578
  8. Jignesh M. Patel, David J. DeWitt: Partition Based Spatial-Merge Join. SIGMOD Conference 1996: 259-270
  9. William O'Connell, Ion Tim Ieong, David Schrader, C. Watson, Grace Au, Alexandros Biliris, S. Choo, P. Colin, G. Linderman, Euthimios Panagos, J. Wang, T. Walters: A Content-Based Multimedia Server for Massively Parallel Architectures. SIGMOD Conference 1996: 68-78
  10. Chris Clifton, Hector Garcia-Molina, David Bloom: HyperFile: A Data and Query Model for Documents. VLDB J. 4(1): 45-86(1995)
  11. Janet L. Wiener, Jeffrey F. Naughton: OODB Bulk Loading Revisited: The Partitioned-List Approach. VLDB 1995: 30-41
  12. David J. DeWitt, Navin Kabra, Jun Luo, Jignesh M. Patel, Jie-Bing Yu: Client-Server Paradise. VLDB 1994: 558-569
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