article

Free access

Interoperability of multiple autonomous databases

Authors:

Witold Litwin,

Leo Mark,

Nick RoussopoulosAuthors Info & Claims

ACM Computing Surveys (CSUR), Volume 22, Issue 3

Pages 267 - 293

https://doi.org/10.1145/96602.96608

Published: 01 September 1990 Publication History

PDF eReader

Abstract

Database systems were a solution to the problem of shared access to heterogeneous files created by multiple autonomous applications in a centralized environment. To make data usage easier, the files were replaced by a globally integrated database. To a large extent, the idea was successful, and many databases are now accessible through local and long-haul networks. Unavoidably, users now need shared access to multiple autonomous databases. The question is what the corresponding methodology should be. Should one reapply the database approach to create globally integrated distributed database systems or should a new approach be introduced?

We argue for a new approach to solving such data management system problems, called multidatabase or federated systems. These systems make databases interoperable, that is, usable without a globally integrated schema. They preserve the autonomy of each database yet support shared access.

Systems of this type will be of major importance in the future. This paper first discusses why this is the case. Then, it presents methodologies for their design. It further shows that major commerical relational database systems are evolving toward multidatabase systems. The paper discusses their capabilities and limitations, presents and discusses a set of prototypes, and, finally, presents some current research issues.

References

[1]

BELLCASTRO, E., et al. 1988. DQS: Distributed query system. (Italy, March 1988). 21st International Conference on Extending Database Technology. vol. 303. Springer Verlag, New York, pp. 770-789.

Crossref

Google Scholar

[2]

BREITBART, Y., AND TIEMAN, L. 1985. ADDS: Heterogeneous Distributed Database System, Distributed Data Sharing Systems, F. Schreiber and W. Litwin, Eds. North-Holland Publishing Co., The Netherlands.

Google Scholar

[3]

BURNS, T., FONG, E., JEFFERSON, D., KNOX, R., REEDY, C., REICH, L., ROUSSOPOULOS, N., AND TRUSZKOWSKI, W. 1986. Reference model for DBMS standardization. ACM SIGMOD Rec. 15, 1 (Mar.), 19-58.

Crossref

Google Scholar

[4]

CHU, W., Ed. 1987. Special issue on distributed database systems. Proc. IEEE 75, 5 (May), 532-735.

Google Scholar

[5]

CONSULTATIVE COMMITTEE FOR SPACE DATA SYS- TEMS. 1987. Standard Formatted Data Units: Structure and Construction Rules. Red Book, Issue 2 (Feb.). National Aeronautics and Space Administration.

Google Scholar

[6]

DATE, C. J. 1986. An Introduction to Database Systems. 4th ed. Vol. 1. Addison-Wesley, Reading, Mass., p. 639.

Crossref

Google Scholar

[7]

FANKHAUSER, P., LITWIN, W., NEUHOLD, E., AND SCHREFL, M. 1988. Global view definition and multidatabase languages: Two approaches to database integration. In Research into Networks and Distributed Applications, R. Speth, Ed. Elsevier North-Holland, New York, pp. 1069-1082.

Google Scholar

[8]

FISHMAN, D., BEECH, D., CATE, H. P., CHOW, E. C., CONNORS, T., DAVIS, J. W., DERRETT, N., HOCH, C. G., KENT, W., LYNGBAEK, P., MAHBAD, B., NEIMAT, M. A., RYAN, T. A., AND SHAN, M. C: "IRIS: An Object-Oriented Database Management System," In Readings in Object-Oriented Database Systems, Zdonik, S., and Maier, D. (Eds). Morgan Kaufmann, San Mateo, Calif., 1990.

Crossref

Google Scholar

[9]

GOMER, T., THOMPSON, G., CHUNG, C-W., BARK- MEYER, E., CARTER, F., TEMPLETON, M., FOX, S., AND HARTMAN, B. 1990. Heterogeneous distributed database systems for production use. A CM Cornput. Surv. In this issue.

Crossref

Google Scholar

[10]

HAMMER, M., AND MCLEOD, D. 1979. On database management system architecture. MIT Lab. for Comp. Sc. MIT/LCS/TM-141. (Oct.), 35.

Google Scholar

[11]

HEIMBIGNER, D. 1987. A Federated System for Software Management. IEEE Data Engineering 10, 3 (Sept. 1987), 39-45.

Google Scholar

[12]

HEIMBIGNER, D., AND MCLEOD, D. 1985. A federated architecture for information management. ACM Trans. Off. Inf. Syst. 3, 3 (July), 253-278.

Crossref

Google Scholar

[13]

International Standards Organization, 1987.

Google Scholar

[14]

Remote Database Access Protocol. 2nd working draft. ISO/TC 97/SC 21/WG 3, 1987.

Google Scholar

[15]

JAKOBSON, G., PIATETSKY-SHAPIRO, G., LAFOND, C., RAJINIKANTH, M., AND HERNANDEZ, J. 1988. CALIDA: A knowledge-based system for integrating multiple heterogeneous databases.In 3rd International Conference on Data and Knowledge Bases: Improving Usability and Responsiveness (Jerusalem, June). Morgan Kaufmann, San Mateo, Calif., pp. 3-18.

Google Scholar

[16]

KRONSJO, L. 1987. Algorithms: Their Complexity and Efficiency. John Wiley & Sons, New York, p. 363.

Crossref

Google Scholar

[17]

KUHN, E., AND LUDWIG, TH. 1988. VIP-MDBS: A logic multidatabase system. In IEEE International Symposium on Databases in Parallel and Distributed Systems. pp 190-207.

Crossref

Google Scholar

[18]

LANDERS, T., AND ROSENBERG, R. 1982. An Overview of Multibase in Distributed Databases, R. J. Schneider, Ed. North-Holland, The Netherlands.

Google Scholar

[19]

LITWIN W. 1984. MALPHA: A relational multidatabase manipulation language. In 1st IEEE Conference on Data Engineering (Los Angeles, Feb.).

Crossref

Google Scholar

[20]

LITWIN, W. 1985. Implicit joins in the multidatabase system MRDSM. IEEE-COMPSAC, 495-504.

Google Scholar

[21]

LITWIN, W., AND ABDELLATIF, A. 1986. Multidatabase Interoperability. IEEE Comput. 19, 12 (Dec.), 10-18.

Crossref

Google Scholar

[22]

LITWIN, W., AND ABDELLATIF, A. 1987. An overview of the multidatabase manipulation language MDSL. Invited paper. Proc. IEEE 75, 5 (May), 621-632.

Google Scholar

[23]

LITWIN, W., AND VIGIER, PH. 1989. New functions for dynamic attributes in the multidatabase system MRDSM. HLSUA Forum XLV (New Orleans, Oct.). pp. 467-475. Also in inf. Sci. 49, 59-101.

Crossref

Google Scholar

[24]

LITWIN, W., AND TIRRI, H. 1988. Flexible Concurrency control using value dates. IEEE Distr. Proc. Techn. Comm. Newsletter. Spec. Issue on Heterogeneous Distributed Database Systems 10, 2 (Nov.), 42-49. Also in integration of Information Systems: Bridging Heterogenous Databases, A. Gupta, Ed. IEEE Press, New York, pp. 221-230.

Google Scholar

[25]

LITWIN, W., et al. 1982. SIRIUS Systems {or Distributed Data Management, H. J. Schneider, Ed. North-Holland Publishing, The Netherlands, pp. 311-366.

Google Scholar

[26]

LITWlN, W., et al. 1987. MSQL: A multidatabase language. INRIA Res. Rep. 695 (June), 41. Inf. Sci.

Google Scholar

[27]

MARK, L. 1985. Self-describing database systems: Formalization and realization. Ph.D. dissertation, CS-TR-1484, Dept. of Computer Science, Univ. of Maryland, College Park, Maryland.

Google Scholar

[28]

MARK, L., AND ROUSSOPOULOS, N. 1987a. Information interchange between self-describing databases. IEEE Data Eng. 10, 3 (Sept.), 46-52.

Google Scholar

[29]

MARK, L., AND ROUSSOPOULOS, N. 1987b. Operational specifications of update dependencies. SRC-TR-87-37, Systems Research Center, Univ. of Maryland, College Park, Maryland. (Feb.), pp. 1-44.

Google Scholar

[30]

MARK, L., ROUSSOPOULOS, N., AND CHU, B. 1985. Update dependencies. IFIP TC2 WG 2.6. Working Conference on Database Semantics (Jan.), Belgium. In Database Semantics, Steel, T.B. and Meersman, R., (Eds). North-Holland, The Netherlands, 1986, pp. 303-319.

Google Scholar

[31]

MOTRO, A. 1987. Superviews: Virtual integration of multiple databases. IEEE Trans. Softw. Eng. 13, 7 (July), 785-798.

Crossref

Google Scholar

[32]

NEUHOLD, E., AND SCHREFL, M. 1988. Dynamic derivation of personalized views. In 14th International Conference on Very Large Data Bases (Los Angeles, Aug.). Morgan Kaufmann, Palo Alto, Calif., pp. 183-194.

Crossref

Google Scholar

[33]

Pu, C. 1987. Superdatabases: Transactions across database boundaries. IEEE Data Eng. 10, 3 (Sept.), 19-25.

Google Scholar

[34]

ROSENTHAL, A., AND CHAKRAVARTHY, U. S. 1988. Anatomy of a modural multiple query optimizer. In 14th International Conference on Very Large Data Bases (Los Angeles, Aug.). Morgan Kaufmann, Palo Alto, Calif., pp. 230-239.

Crossref

Google Scholar

[35]

ROUSSOPOULOS, N. 1983. Intensional semantics of a self-documenting relational model. CS-TR- 1264, Dept. of Computer Science, Univ. of Maryland, College Park.

Google Scholar

[36]

ROUSSOPOULOS, N. 1987. Overview of ADMS: A high performance database management system. Invited Paper. In Fall Joint Computer Conference (Dallas, Texas, Oct.), pp. 25-29. IEEE Computer Society Press, New York.

Crossref

Google Scholar

[37]

ROUSSOPOULOS, N., AND gANG, H. 1986. Principles and techniques in the design of ADMS_. IEEE Comput. Mag. 19, 12 (Dec.), 19-25.

Crossref

Google Scholar

[38]

ROUSSOPOULOS, N., AND MARK, L. 1984. Update dependencies in relational databases. In i st international Conference on Expert Database Systems (Kiawah Island, S.C., Oct.), Kerschberg, L. Ed. Sponsored by University of South Carolina and ACM-SIDMOD and SIGART.

Google Scholar

[39]

ROUSSOPOULOS, N., AND MARK, L. 1985. Schema manipulation in self-describing and selfdocumenting data models. Int. J. Comput. Inf. Sci. 14, 1, 1-28.

Google Scholar

[40]

ROUSSOPOULOS, N., AND WALLACE, S. 1982. Self description vs. self-documentation. Workshop on self-describing data structures, Univ. of Maryland, College Park.

Google Scholar

[41]

RUSINKIEWICZ, M., AND CZEJDO, B. 1987. An approach to query processing in federated database systems. In Proceedings of the 20th International Conference on System Sciences (Hawaii, Jan.), pp. 430-440.

Google Scholar

[42]

SARIS, S., Ed. 1987. Special issue on federated database systems. IEEE Data Eng. 10, 3 (Sept.), 64.

Google Scholar

[43]

SELLIS, T. 1988. Multiple queries optimization. A CM Trans. Database Syst. 13, 1, 23-52.

Crossref

Google Scholar

[44]

SHAN, M. (N. d.) Unified access in a heterogeneous information environment. Special issue on information sharing in heterogeneous database systems. IEEE Office Knowledge Engineering. To be published.

Google Scholar

[45]

SHETH, A., AND LARSON, J. 1990. Federated database systems for managing distributed, heterogeneous and autonomous databases. ACM Comput. Surv. In this issue.

Crossref

Google Scholar

[46]

STANISZKIS, W., KAMINSKI, W., ET AL. 1985. Architecture of the Network Data Management Systems, F. Schreiber and W. Litwin, Eds. North- Holland, The Netherlands.

Google Scholar

[47]

STONEBRAKER, M. 1975. Implementation of integrity constraints and views by query modification. No. ERL-M514. Electronics Res. Lab., College of Engineering, Univ. of California, Berkeley.

Google Scholar

[48]

TEMPLETON, M., LUND, E., AND WARD, P. 1987b. Pragmatics of access control in Mermaid. IEEE Data Eng. 10, 3 (Sept.), 33-38.

Google Scholar

[49]

TEMPLETON, M., BRILL, D., CHEN, A., DAO, S., LUND, E., MCGREGOR, R., AND WARD, P. Mermaid: A front-end to distributed heterogeneous databases. Proc. IEEE 75, 5 (May), 695-708.

Google Scholar

[50]

WOLSKI, A. 1989. LINDA: A system for loosely integrated databases. In 5th IEEE Conference on Data Engineering (Los Angeles).

Crossref

Google Scholar

Cited By

View all

Gutiérrez YSalas JMontoyo AMuñoz REstévez-Velarde S(2024)KD SENSO-MERGER: An architecture for semantic integration of heterogeneous dataEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.107854132(107854)Online publication date: Jun-2024
https://doi.org/10.1016/j.engappai.2024.107854
Dang VAussenac-Gilles NMegdiche IRavat F(2024)Enabling Interdisciplinary Research in Open Science: Open Science Data NetworkResearch Challenges in Information Science10.1007/978-3-031-59465-6_2(19-34)Online publication date: 2-May-2024
https://doi.org/10.1007/978-3-031-59465-6_2
Belchior RRiley LHardjono TVasconcelos ACorreia M(2023)Do You Need a Distributed Ledger Technology Interoperability Solution?Distributed Ledger Technologies: Research and Practice10.1145/35645322:1(1-37)Online publication date: 14-Mar-2023
https://dl.acm.org/doi/10.1145/3564532
Show More Cited By

Recommendations

Supporting interoperability of autonomous hospital databases: a case study
ADBIS'97: Proceedings of the First East-European conference on Advances in Databases and Information systems

We describe an approach that supports distributed information discovery when interoperating with large number of autonomous hospital databases. The approach is presented through a case study based on the health care network. The idea is to perform ...
NoSQL databases: MongoDB vs cassandra
C3S2E '13: Proceedings of the International C* Conference on Computer Science and Software Engineering

In the past, relational databases were used in a large scope of applications due to their rich set of features, query capabilities and transaction management. However, they are not able to store and process big data effectively and are not very ...
Managing change in heterogeneous autonomous databases

Reviews

Reviewer: Fazli Can

Multidatabases (MDBs) or interoperable databases are multiple autonomous databases managed together. Unlike a distributed database management system (DDBMS), they do not have a single global conceptual schema. In many cases, database users resist integration and would like to preserve the autonomy of their databases. MDB is a natural answer to this user tendency. The authors of this survey paper first discuss general characteristics of MDBs, then describe how existing information retrieval (IR) and videotex databases provide for interoperability. Not surprisingly, due to the relatively simple nature of the update operations of IR systems and the availability of many online IR databases, large-scale MDBs for document retrieval are already available. The paper provides examples of them. Next, the authors present two methodologies for the design of MDB systems and discuss the relationships between these approaches and the DDBMSs. Later, they give examples of the MDB capabilities of commercial relational database and IR systems and several prototypes developed in different settings. Finally, they provide pointers for future research. These include self-documenting database systems, update problems, query processing, knowledge basis, data models, and dynamic viewing. This paper and the other papers published in the same special issue of ACM Computing Surveys on heterogeneous databases [1,2] are beneficial to a large spectrum of people, ranging from nondatabase specialists to researchers who are interested in this application of databases. The papers also unify the terms and concepts used and try to provide a basis for future research.

Access critical reviews of Computing literature here

Become a reviewer for Computing Reviews.

Comments

Information & Contributors

Information

Published In

ACM Computing Surveys Volume 22, Issue 3

Special issue on heterogeneous databases

Sept. 1990

111 pages

ISSN:0360-0300

EISSN:1557-7341

DOI:10.1145/96602

Issue’s Table of Contents

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 01 September 1990

Published in CSUR Volume 22, Issue 3

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Qualifiers

Article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

320
Total Citations
View Citations
3,203
Total Downloads

Downloads (Last 12 months)211
Downloads (Last 6 weeks)18

Reflects downloads up to 24 Oct 2024

Other Metrics

View Author Metrics

Citations

Cited By

View all

Gutiérrez YSalas JMontoyo AMuñoz REstévez-Velarde S(2024)KD SENSO-MERGER: An architecture for semantic integration of heterogeneous dataEngineering Applications of Artificial Intelligence10.1016/j.engappai.2024.107854132(107854)Online publication date: Jun-2024
https://doi.org/10.1016/j.engappai.2024.107854
Dang VAussenac-Gilles NMegdiche IRavat F(2024)Enabling Interdisciplinary Research in Open Science: Open Science Data NetworkResearch Challenges in Information Science10.1007/978-3-031-59465-6_2(19-34)Online publication date: 2-May-2024
https://doi.org/10.1007/978-3-031-59465-6_2
Belchior RRiley LHardjono TVasconcelos ACorreia M(2023)Do You Need a Distributed Ledger Technology Interoperability Solution?Distributed Ledger Technologies: Research and Practice10.1145/35645322:1(1-37)Online publication date: 14-Mar-2023
https://dl.acm.org/doi/10.1145/3564532
Nasfi RBronselaer ADe Tré G(2023)A novel approach to assess and improve syntactic interoperability in data integrationInformation Processing & Management10.1016/j.ipm.2023.10352260:6(103522)Online publication date: Nov-2023
https://doi.org/10.1016/j.ipm.2023.103522
Daniel SBernd BDavid R(2023)Privacy-preserving and lossless distributed estimation of high-dimensional generalized additive mixed modelsStatistics and Computing10.1007/s11222-023-10323-234:1Online publication date: 7-Nov-2023
https://dl.acm.org/doi/10.1007/s11222-023-10323-2
Reznichenko V(2022)60 Years of Databases (part three)PROBLEMS IN PROGRAMMING10.15407/pp2022.01.034(034-066)Online publication date: Mar-2022
https://doi.org/10.15407/pp2022.01.034
Hodapp DHanelt A(2022)Interoperability in the era of digital innovation: An information systems research agendaJournal of Information Technology10.1177/0268396221106430437:4(407-427)Online publication date: 7-Feb-2022
https://doi.org/10.1177/02683962211064304
Kim HTuresson HLaskowski MBahreini A(2022)Permissionless and Permissioned, Technology-Focused and Business Needs-Driven: Understanding the Hybrid Opportunity in Blockchain Through a Case Study of InsolarIEEE Transactions on Engineering Management10.1109/TEM.2020.300356569:3(776-791)Online publication date: Jun-2022
https://doi.org/10.1109/TEM.2020.3003565
Bellanova RGlouftsios G(2022)Formatting European security integration through database interoperabilityEuropean Security10.1080/09662839.2022.210188631:3(454-474)Online publication date: 9-Sep-2022
https://doi.org/10.1080/09662839.2022.2101886
Atan RAzram N(2019)A Framework for Halal Knowledge Metadata RepresentationsApplied Mechanics and Materials10.4028/www.scientific.net/AMM.892.8892(8-15)Online publication date: Jun-2019
https://doi.org/10.4028/www.scientific.net/AMM.892.8
Show More Cited By

View Options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Abstract

References

Cited By

Recommendations

Supporting interoperability of autonomous hospital databases: a case study

NoSQL databases: MongoDB vs cassandra

Managing change in heterogeneous autonomous databases

Reviews

Access critical reviews of Computing literature here

Comments

Information

Published In

Publisher

Publication History

Permissions

Check for updates

Qualifiers

Contributors

Other Metrics

Bibliometrics

Article Metrics

Other Metrics

Citations

Cited By

View options

PDF

eReader

Get Access

Login options

Full Access

Figures

Other

Share

Share this Publication link

Share on social media

Affiliations