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The Revolution in Database Architecture
March 1, 2004
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BibTex
Authors

Jim Gray
Publication Type
TechReport
Pages
4
Number
MSR-TR-2004-31
Publisher
Association for Computing Machinery, Inc.
Copyright © 2004 by the Association for Computing Machinery, Inc. Permission to make
digital or hard copies of part or all of this work for personal or classroom use is granted without
fee provided that copies are not made or distributed for profit or commercial advantage and that
copies bear this notice and the full citation on the first page. Copyrights for components of this
work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy
otherwise, to republish, to post on servers, or to redistribute to lists, requires prior specific
permission and/or a fee. Request permissions from Publications Dept, ACM Inc., fax +1 (212)
869-0481, or permissions@acm.org. The definitive version of this paper can be found at
ACM’s Digital Library –http://www.acm.org/dl/.

Abstract
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Related Info
Abstract
Database system architectures are undergoing revolutionary changes. Most importantly,
algorithms and data are being unified by integrating programming languages with the database
system. This gives an extensible object-relational system where non-procedural relational
operators manipulate object sets. Coupled with this, each DBMS is now a web service. This has
huge impli-cations for how we structure applications. DBMSs are now object containers. Queues
are the first objects to be added. These queues are the basis for transaction processing and
workflow applica-tions. Future workflow systems are likely to be built on this core. Data cubes
and online analytic processing are now baked into most DBMSs. Beyond that, DBMSs have a
framework for data mining and machine learning algorithms. Decision trees, Bayes nets,
clustering, and time series analysis are built in; new algo-rithms can be added. There is a rebirth
of column stores for sparse tables and to optimize bandwidth. Text, temporal, and spatial data
access methods, along with their probabilistic reasoning have been added to database systems.
Allowing approximate and prob-abilistic answers is essential for many applications. Many
believe that XML and xQuery will be the main data structure and access pattern. Database
systems must accommodate that perspective. External data increasingly arrives as streams to be
compared to historical data; so stream-processing operators are being added to the DBMS.
Publish-subscribe systems invert the data-query ra-tios; incoming data is compared against
millions of queries rather than queries searching millions of records. Meanwhile, disk and
memory capacities are growing much faster than their bandwidth and latency, so the database
systems increasingly use huge main memories and sequential disk access. These changes
mandate a much more dynamic query optimization strategy – one that adapts to current
conditions and selectivities rather than having a static plan. Intelligence is moving to the
periphery of the network. Each disk and each sensor will be a competent database machine.
Relational algebra is a convenient way to program these systems. Database systems are now
expected to be self-managing, self-healing, and always-up. We researchers and developers have
our work cut out for us in delivering all these features.
Related Info
Related Files
 tr-2004-31.doc
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