Managing Temporal Financial Data in an Extensible Database.
Rakesh Chandra, Arie Segev:
Managing Temporal Financial Data in an Extensible Database.
VLDB 1993: 302-313@inproceedings{DBLP:conf/vldb/ChandraS93,
author = {Rakesh Chandra and
Arie Segev},
editor = {Rakesh Agrawal and
Se{\'a}n Baker and
David A. Bell},
title = {Managing Temporal Financial Data in an Extensible Database},
booktitle = {19th International Conference on Very Large Data Bases, August
24-27, 1993, Dublin, Ireland, Proceedings},
publisher = {Morgan Kaufmann},
year = {1993},
isbn = {1-55860-152-X},
pages = {302-313},
ee = {db/conf/vldb/ChandraS93.html},
crossref = {DBLP:conf/vldb/93},
bibsource = {DBLP, http://dblp.uni-trier.de}
}
Abstract
Complex financial products and trading applications are difficult to model and implement in conventional commercial databases due to temporal, object, rule and other data support requirements.
Extensible database systems provide a better solution because of the ability todefine complex data types, manipulate data of type procedure, define rules, operators and access methods to optimize these operators.
The paper discusses the design issues in modeling financial trading systems in extensible DBMS.
The complexity of financial products is analyzed and strategies for modeling these products are proposed.
Operators relevant to financial trading are discussed alongwith access methods to optimize these operators.
The paper describes an implementation of a financial trading system in POSTGRES.
Copyright © 1993 by the VLDB Endowment.
Permission to copy without fee all or part of this material is granted provided that the copies are not made or
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is by the permission of the Very Large Data Base
Endowment. To copy otherwise, or to republish, requires
a fee and/or special permission from the Endowment.
Online Paper
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Printed Edition
Rakesh Agrawal, Seán Baker, David A. Bell (Eds.):
19th International Conference on Very Large Data Bases, August 24-27, 1993, Dublin, Ireland, Proceedings.
Morgan Kaufmann 1993, ISBN 1-55860-152-X
Contents 
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Referenced by
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Using SQL to Build New Aggregates and Extenders for Object- Relational Systems.
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An EER-Based Conceptual Model and Query Language for Time-Series Data.
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