Skip to main content

Towards a Systematic Benchmark for Array Database Systems

  • Conference paper

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 8163))

Abstract

Big Data are a central challenge today in science and industry. Typically, Big Data are characterized from application perspectives. From a data structure perspective, among the core structures appearing are sets, graphs, and arrays. In particular in science and engineering we find arrays being a main contributor to data volumes. In fact, large, multi-dimensional arrays represent an important information category in earth, life, and space sciences, but also in engineering, business, and e-government.

Having long been neglected by database research, arrays today increasingly receive attention leading to a whole new field of investigation, Array Databases. As more and more Arry Database Systems emerge, similarities and differences can be observed. This calls for complementary research on benchmarks for Array DBMSs.

We present work in progress on such a comprehensive Array DBMS benchmark, which is based on our 15 years of pioneering Array DBMSs and also designing a geo raster query language standard and its corresponding functionality benchmark.

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   49.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. MySQL, http://www.mysql.com/

  2. OGC Compliance Testing, http://www.opengeospatial.org/compliance

  3. OpenNdap, http://www.openndap.org

  4. Baumann, P., Jucovschi, C., Stancu-Mara, S.: Efficient map portrayal using a general-purpose query language (a case study). In: Bhowmick, S.S., Küng, J., Wagner, R. (eds.) DEXA 2009. LNCS, vol. 5690, pp. 153–163. Springer, Heidelberg (2009)

    Chapter  Google Scholar 

  5. Baumann, P. (ed.): Web Coverage Processing Service (WCPS) Implementation Specification. No. 08-068r2, OGC, 1.0.0 edn. (2008)

    Google Scholar 

  6. Baumann, P.: Beyond rasters: introducing the new OGC web coverage service 2.0. In: Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2010, pp. 320–329. ACM, New York (2010), http://doi.acm.org/10.1145/1869790.1869835

    Google Scholar 

  7. Baumann, P.: The OGC web coverage processing service (WCPS) standard. Geoinformatica 14(4), 447–479 (2010), http://dx.doi.org/10.1007/s10707-009-0087-2

    Article  MathSciNet  Google Scholar 

  8. Baumann, P.: A database array algebra for spatio-temporal data and beyond. In: Pinter, R., Tsur, S. (eds.) NGITS 1999. LNCS, vol. 1649, pp. 76–93. Springer, Heidelberg (1999)

    Chapter  Google Scholar 

  9. Chock, M., Cardenas, A.F., Klinger, A.: Database structure and manipulation capabilities of a picture database management system (picdms). IEEE Transactions on Pattern Analysis and Machine Intelligence 6(4), 484–492 (1984)

    Article  Google Scholar 

  10. Council Transaction Processing Performance, TPC C Benchmark (2010), Standard Specification, http://www.tpc.org/tpcc/spec/tpcc_current.pdf

  11. Cudre-Mauroux, P., Kimura, H., Lim, K.T., Rogers, J., Madden, S., Stonebraker, M., Zdonik, S., Brown, P.: SS-DB: A standard science DBMS benchmark (2010)

    Google Scholar 

  12. Cudre-Mauroux, P., Kimura, H., Lim, K.T., Rogers, J., Simakov, R., Soroush, E., Velikhov, P., Wang, D.L., Balazinska, M., Becla, J., DeWitt, D., Heath, B., Maier, D., Madden, S., Patel, J., Stonebraker, M., Zdonik, S.: A demonstration of SciDB: a science-oriented DBMS. Proc. VLDB Endow. 2(2), 1534–1537 (2009), http://dl.acm.org/citation.cfm?id=1687553.1687584

    Google Scholar 

  13. Garcia, A., Baumann, P.: Modeling fundamental geo-raster operations with array algebra. In: Proc. IEEE SSTDM, October 28-31, pp. 607–612 (2007)

    Google Scholar 

  14. ISO9075:1999: Information Technology-Database Language SQL. Standard No. ISO/IEC 9075:1999, International Organization for Standardization (ISO) (1999), (Available from American National Standards Institute, New York, NY 10036, (212) 642-4900)

    Google Scholar 

  15. Joachims, T.: Text categorization with support vector machines: Learning with many relevant features. In: Nédellec, C., Rouveirol, C. (eds.) ECML 1998. LNCS, vol. 1398, pp. 137–142. Springer, Heidelberg (1998), http://dx.doi.org/10.1007/BFb0026683

    Chapter  Google Scholar 

  16. Kersten, M.L., Zhang, Y., Ivanova, M., Nes, N.: SciQL, a query language for science applications. In: Baumann, P., Howe, B., Orsborn, K., Stefanova, S. (eds.) EDBT/ICDT Array Databases Workshop, pp. 1–12. ACM (2011), http://dblp.uni-trier.de/db/conf/edbt/array2011.html#KerstenZIN11

  17. Kimball, R., Caserta, J.: The data warehouse ETL toolkit. John Wiley & Sons (2004)

    Google Scholar 

  18. LSIS Research Group Jacobs University. The array database rasdaman, Rasdaman is available at http://www.rasdaman.org

  19. MATLAB: version (R2013a). Natick, Massachusetts (2013)

    Google Scholar 

  20. Patel, J.M., Yu, J.B., Kabra, N., Tufte, K., Nag, B., Burger, J., Hall, N.E., Ramasamy, K., Lueder, R., Ellmann, C.J., Kupsch, J., Guo, S., DeWitt, D.J., Naughton, J.F.: Building a Scaleable Geo-Spatial DBMS: Technology, Implementation, and Evaluation. In: Peckham, J. (ed.) SIGMOD Conference, pp. 336–347. ACM Press (1997), http://doi.acm.org/10.1145/253260.253342

  21. Pisarev, A., Poustelnikova, E., Samsonova, M., Baumann, P.: Mooshka: a system for the management of multidimensional gene expression data in situ. Inf. Syst. 28(4), 269–285 (2003), http://dx.doi.org/10.1016/S0306-43790200074-1

    Google Scholar 

  22. PostGIS, http://www.postgis.org

  23. R Core Team: R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria (2013), http://www.R-project.org

  24. Stonebraker, M., Brown, P., Poliakov, A., Raman, S.: The architecture of SciDB. In: Bayard Cushing, J., French, J., Bowers, S. (eds.) SSDBM 2011. LNCS, vol. 6809, pp. 1–16. Springer, Heidelberg (2011), http://dl.acm.org/citation.cfm?id=2032397.2032399

    Chapter  Google Scholar 

  25. Stonebraker, M., Frew, J., Gardels, K., Meredith, J.: The Sequoia 2000 Benchmark. In: Buneman, P., Jajodia, S. (eds.) SIGMOD Conference, pp. 2–11. ACM Press (1993), http://doi.acm.org/10.1145/170035.170038

  26. The Standard Performance Evaluation Corporation. SPEC Benchmark (2012), http://www.spec.org/benchmarks.html

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Baumann, P., Stamerjohanns, H. (2014). Towards a Systematic Benchmark for Array Database Systems. In: Rabl, T., Poess, M., Baru, C., Jacobsen, HA. (eds) Specifying Big Data Benchmarks. WBDB WBDB 2012 2012. Lecture Notes in Computer Science, vol 8163. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53974-9_9

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-53974-9_9

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-53973-2

  • Online ISBN: 978-3-642-53974-9

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics