A Universal Cuboid-Based Integration Architecture for Polyglotic Querying of Heterogeneous Datasources

  • Michał Chromiak
  • Piotr Wiśniewski
  • Krzysztof Stencel
Part of the Communications in Computer and Information Science book series (CCIS, volume 521)


Fortunately, the industry has eventually abandoned the old “one-size fits all” relational dream and started to develop task-oriented storage solutions. Nowadays, in a big project a devotion to a single persistence mechanism usually leads to suboptimal architectures. A combination of appropriate storage engines is often the best solution. However, such a combination implies a significant growth of data integrity maintenance. In this paper we describe a solution to this problem, i.e. a cuboid-based universal integration architecture. It allows hiding the peculiarities of integration so that it is transparent to the application programmer. We use graphs as an example of data that needs a task-oriented database in order to be efficiently processed. We show how graph queries can be effectively executed with the help of a graph database assisting a relational database. The proposed solution does not impose any additional complexity for programmers.


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  1. 1.
    Burzańska, M., Stencel, K., Suchomska, P., Szumowska, A., Wiśniewski, P.: Recursive queries using object relational mapping. In: Kim, T.-H., Lee, Y.-H., Kang, B.-H., Ślęzak, D. (eds.) FGIT 2010. LNCS, vol. 6485, pp. 42–50. Springer, Heidelberg (2010)CrossRefGoogle Scholar
  2. 2.
    Burzańska, M., Stencel, K., Wiśniewski, P.: Pushing predicates into recursive SQL common table expressions. In: Grundspenkis, J., Morzy, T., Vossen, G. (eds.) ADBIS 2009. LNCS, vol. 5739, pp. 194–205. Springer, Heidelberg (2009)CrossRefGoogle Scholar
  3. 3.
    Chromiak, M., Stencel, K.: The linkup data structure for heterogeneous data integration platform. In: Kim, T.-H., Lee, Y.-h., Fang, W.-C. (eds.) FGIT 2012. LNCS, vol. 7709, pp. 263–274. Springer, Heidelberg (2012), http://dx.doi.org/10.1007/978-3-642-35585-1_36 CrossRefGoogle Scholar
  4. 4.
    Chromiak, M., Stencel, K.: A data model for heterogeneous data integration architecture. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B. (eds.) BDAS 2014. CCIS, vol. 424, pp. 547–556. Springer, Heidelberg (2014), http://dx.doi.org/10.1007/978-3-319-06932-6_53 CrossRefGoogle Scholar
  5. 5.
    Chromiak, M., Wisniewski, P., Stencel, K.: Exploiting order dependencies on primary keys for optimization. In: Proceedings of the 23rd International Workshop on Concurrency, Specification and Programming, Chemnitz, Germany, September 29 - October 1, pp. 58–68 (2014), http://ceur-ws.org/Vol-1269/paper58.pdf (accessed: February 06, 2015)
  6. 6.
    Cloudkick: 4 months with Cassandra, a love story (March 2010), https://www.cloudkick.com/blog/2010/mar/02/4_months_with_cassandra/ (accessed: November 12, 2013)
  7. 7.
    Ghazal, A., Crolotte, A., Seid, D.Y.: Recursive SQL query optimization with k-iteration lookahead. In: Bressan, S., Küng, J., Wagner, R. (eds.) DEXA 2006. LNCS, vol. 4080, pp. 348–357. Springer, Heidelberg (2006)CrossRefGoogle Scholar
  8. 8.
    Holzschuher, F., Peinl, R.: Performance of graph query languages: Comparison of cypher, gremlin and native access in neo4j. In: EDBT/ICDT 2013, pp. 195–204. ACM, New York (2013), http://doi.acm.org/10.1145/2457317.2457351 Google Scholar
  9. 9.
    Hunger, M.: Load csv with success (2014), http://jexp.de/blog/2014/10/load-cvs-with-success/(accessed: February 06, 2015)
  10. 10.
    Neo4j: Load csv into neo4j quickly and successfully (2014), http://jexp.de/blog/2014/06/load-csv-into-neo4j-quickly-and-successfully/ (accessed: February 06, 2015)
  11. 11.
    Ordonez, C.: Optimization of linear recursive queries in sql. IEEE Trans. Knowl. Data Eng. 22(2), 264–277 (2010)CrossRefMathSciNetGoogle Scholar
  12. 12.
    Plugge, E., Hawkins, T., Membrey, P.: The Definitive Guide to MongoDB: The NoSQL Database for Cloud and Desktop Computing, 1st edn. Apress, Berkely (2010)CrossRefGoogle Scholar
  13. 13.
    Przymus, P., Boniewicz, A., Burzańska, M., Stencel, K.: Recursive query facilities in relational databases: A survey. In: FGIT-DTA/BSBT, pp. 89–99 (2010)Google Scholar
  14. 14.
    Szumowska, A., Burzańska, M., Wiśniewski, P., Stencel, K.: Efficient implementation of recursive queries in major object relational mapping systems. In: Kim, T.-h., Adeli, H., Slezak, D., Sandnes, F.E., Song, X., Chung, K.-i., Arnett, K.P. (eds.) FGIT 2011. LNCS, vol. 7105, pp. 78–89. Springer, Heidelberg (2011)CrossRefGoogle Scholar
  15. 15.
    Szumowska, A., Burzańska, M., Wiśniewski, P., Stencel, K.: Extending HQL with plain recursive facilities. In: Morzy, T., Härder, T., Wrembel, R. (eds.) Advances in Databases and Information Systems. AISC, vol. 186, pp. 265–272. Springer, Heidelberg (2013)CrossRefGoogle Scholar
  16. 16.
    Van Bruggen, R.: Learning Neo4j. Packt, Birmingham (2014)Google Scholar
  17. 17.
    Wiśniewski, P., Szumowska, A., Burzańska, M., Boniewicz, A.: Hibernate the recursive queries - defining the recursive queries using Hibernate ORM. In: ADBIS (2), pp. 190–199 (2011)Google Scholar

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© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Michał Chromiak
    • 1
  • Piotr Wiśniewski
    • 2
  • Krzysztof Stencel
    • 3
  1. 1.Institute of InformaticsMaria Curie Skłodowska UniversityLublinPoland
  2. 2.Faculty of Mathematics and Computer ScienceNicolaus Copernicus UniversityToruńPoland
  3. 3.Institute of InformaticsUniversity of WarsawWarsawPoland

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