7758508
Implementing the spirit of SQL-99
This paper describes the current INFORMIX IDS/UD release (9.2 or Centaur) and compares and contrasts its functionality with the features of the SQL-99 language standard. INFORMIX and Illustra have been shipping DBMSs implementing the spirit of the SQL-99 standard for five years. In this paper, we review our experience working with ORDBMS technology, and argue that while SQL-99 is a huge improvement over SQL-92, substantial further work is necessary to make object-relational DBMSs truly useful. Specifically, we describe several interesting pieces of functionality unique to IDS/UD, and several dilemmas our customers have encountered that the standard does not address.
2984369
BigSur: A System For the Management of Earth Science Data
In this paper we present a prototype system for the management of earth science data which is novel in that it takes a DBMS centric view of the the task. Our prototype -called "BigSur" -is shown in the context of its use by two geographically distributed scientific groups with demanding data storage and processing requirements. BigSur currently stores 1 Terabyte of data, about one thousandth of the volume EOSDIS must store. We claim that the design principles embodied in BigSur provide sufficient flexibility to achieve the difficult scientific and technical objectives of Mission to Planet Earth.
5349915
Distributed Component Database Management Systems
Publisher Summary A component database management system (DBMS) is a system software framework that application developers can extend by embedding modules of programming logic in it. These extensions implement database objects such as new data types, application-level object classes, analytic algorithms, and external data-access facilities. This chapter describes how distributed object relational database management systems (ORDBMSs) are constructed and how they can be used. Distributed component DBMSs such as ORDBMSs are useful because they address requirements that are not served well by traditional distributed systems technologies. Distributed ORDBMSs constitute a powerful, innovative model for generalized distributed computing. It is a unique technology that provides a framework for managing both logic and data in an abstract data model. This review is useful because the commercial versions of distributed ORDBMSs take such a system as a starting point and because detailed descriptions of ORDBMS internals are not widely available. Instances of these single-site ORDBMSs run on each node of the overall distributed system. Furthermore, this chapter outlines the architecture of a distributed ORDBMS and describes the modifications that are necessary for a single-site ORDBMS to operate in a distributed environment.
61130489
Object-Relational DBMSs: Tracking the Next Great Wave
From the Publisher: 
Discover why object-relational technology is ideal for supporting a broad spectrum of data types and application areas, from financial services to multimedia data. In this completely revised and updated edition, database experts Michael Stonebraker and Paul Brown explore the object-relational paradigm and examine the most recent developments in the field. Specially written for database application programmers, database analysts, and IT managers, this book includes detailed information on how to classify DBMS applications, where object-relational DBMSs fit in the database world, and what mechanisms are required to support such an engine.
12789110
Interoperability, Distributed Applications and Distributed Databases: The Virtual Table Interface
Users of distributed databases and of distributed application frameworks require interoperation of heterogeneous data and components, respectively. In this paper, we examine how an extensible, objectrelational database system can integrate both modes of interoperability. We describe the Virtual Table Interface, a facility of the INFORMIX-Dynamic Server Universal Data Option, that provides simplified access to heterogeneous components and discuss the benefits of integrating data with application components.
209399498
The BUCKY Object-Relational Benchmark (Experience Paper).
16124888
GORDIAN: efficient and scalable discovery of composite keys
Identification of (composite) key attributes is of fundamental importance for many different data management tasks such as data modeling, data integration, anomaly detection, query formulation, query optimization, and indexing. However, information about keys is often missing or incomplete in many real-world database scenarios. Surprisingly, the fundamental problem of automatic key discovery has received little attention in the existing literature. Existing solutions ignore composite keys, due to the complexity associated with their discovery. Even for simple keys, current algorithms take a brute-force approach; the resulting exponential CPU and memory requirements limit the applicability of these methods to small datasets. In this paper, we describe GORDIAN, a scalable algorithm for automatic discovery of keys in large datasets, including composite keys. GORDIAN can provide exact results very efficiently for both real-world and synthetic datasets. GORDIAN can be used to find (composite) key attributes in any collection of entities, e.g., key column-groups in relational data, or key leaf-node sets in a collection of XML documents with a common schema. We show empirically that GORDIAN can be combined with sampling to efficiently obtain high quality sets of approximate keys even in very large datasets.
5310188
My gasket
28751129
Facilitating innovative faculty projects: an information technology perspective
The Center for Instruction, Research, and Technology (CIRT) at Indiana State University assists faculty with integration of emerging and innovative technologies into their instruction and research activities. This support ranges from High Performance Computing (HPC) to visualization services. CIRT also provides academic programming support to the University community. Additionally, one of the center's main goals is to continually explore and evaluate new and emerging technologies to support teaching, research, and student learning. This paper covers an internal grant program established by the center, the process of working with faculty on research proposals, and descriptions of several projects developed by CIRT for faculty.
17228561
DAMIA - A Data Mashup Fabric for Intranet Applications
Damia is a lightweight enterprise data integration service where line of business users can create and catalog high value data feeds for consumption by situational applications. Damia is inspired by the Web 2.0 mashup phenomenon. It consists of (1) a browser-based user-interface that allows for the specification of data mashups as data flowfgraphs using a set of operators, (2) a server with an execution engine, as well as (3) APIs for searching, debugging, executing and managing mashups. Damia offers a framework and functionality for dynamic entity resolution, streaming and other higher value features particularly important in the enterprise domain. Damia is currently in perpetual beta in the IBM Intranet. 
 
In this demonstration, we showcase the creation and execution of several enterprise data mashups, thereby illustrating the architecture and features of the overall Damia system.
17356153
CORDS: automatic discovery of correlations and soft functional dependencies
The rich dependency structure found in the columns of real-world relational databases can be exploited to great advantage, but can also cause query optimizers---which usually assume that columns are statistically independent---to underestimate the selectivities of conjunctive predicates by orders of magnitude. We introduce CORDS, an efficient and scalable tool for automatic discovery of correlations and soft functional dependencies between columns. CORDS searches for column pairs that might have interesting and useful dependency relations by systematically enumerating candidate pairs and simultaneously pruning unpromising candidates using a flexible set of heuristics. A robust chi-squared analysis is applied to a sample of column values in order to identify correlations, and the number of distinct values in the sampled columns is analyzed to detect soft functional dependencies. CORDS can be used as a data mining tool, producing dependency graphs that are of intrinsic interest. We focus primarily on the use of CORDS in query optimization. Specifically, CORDS recommends groups of columns on which to maintain certain simple joint statistics. These "column-group" statistics are then used by the optimizer to avoid naive selectivity estimates based on inappropriate independence assumptions. This approach, because of its simplicity and judicious use of sampling, is relatively easy to implement in existing commercial systems, has very low overhead, and scales well to the large numbers of columns and large table sizes found in real-world databases. Experiments with a prototype implementation show that the use of CORDS in query optimization can speed up query execution times by an order of magnitude. CORDS can be used in tandem with query feedback systems such as the LEO learning optimizer, leveraging the infrastructure of such systems to correct bad selectivity estimates and ameliorating the poor performance of feedback systems during slow learning phases.