Parallel Database Systems

  • M. Tamer Özsu
  • Patrick Valduriez


Many data-intensive applications require support for very large databases (e.g., hundreds of terabytes or exabytes). Supporting very large databases efficiently for either OLTP or OLAP can be addressed by combining parallel computing and distributed database management.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Abadi, D. J., Carney, D., Çetintemel, U., Cherniack, M., Convey, C., Lee, S., Stonebraker, M., Tatbul, N., and Zdonik, S. (2003). Aurora: a new model and architecture for data stream management. VLDB J., 12 (2): 120–139.CrossRefGoogle Scholar
  2. Abadi, D. J., Ahmad, Y., Balazinska, M., Çetintemel, U., Cherniack, M., Hwang, J.-H., Lindner, W., Maskey, A., Rasin, A., Ryvkina, E., Tatbul, N., Xing, Y., and Zdonik, S. B. (2005). The design of the Borealis stream processing engine. In Proc. 2nd Biennial Conf. on Innovative Data Systems Research, pages 277–289.Google Scholar
  3. Abadi, D. J., Marcus, A., Madden, S. R., and Hollenbach, K. (2007). Scalable semantic web data management using vertical partitioning. In Proc. 33rd Int. Conf. on Very Large Data Bases, pages 411–422.Google Scholar
  4. Abadi, D. J., Marcus, A., Madden, S., and Hollenbach, K. (2009). SW-Store: a vertically partitioned DBMS for semantic web data management. VLDB J., 18 (2): 385–406.CrossRefGoogle Scholar
  5. Aberer, K. (2001). P-grid: A self-organizing access structure for P2P information systems. In Proc. Int. Conf. on Cooperative Inf. Syst., pages 179–194.Google Scholar
  6. Aberer, K. (2003). Guest editor’s introduction. ACM SIGMOD Rec., 32 (3): 21–22.CrossRefGoogle Scholar
  7. Aberer, K., Cudré-Mauroux, P., Datta, A., Despotovic, Z., Hauswirth, M., Punceva, M., and Schmidt, R. (2003a). P-grid: a self-organizing structured P2P system. ACM SIGMOD Rec., 32 (3): 29–33.CrossRefGoogle Scholar
  8. Aberer, K., Cudré-Mauroux, P., and Hauswirth, M. (2003b). Start making sense: The chatty web approach for global semantic agreements. J. Web Semantics, 1 (1): 89–114.CrossRefGoogle Scholar
  9. Abiteboul, S., Quass, D., McHugh, J., Widom, J., and Wiener, J. (1997). The Lorel query language for semistructured data. Int. J. Digit. Libr., 1 (1): 68–88.CrossRefGoogle Scholar
  10. Abiteboul, S., Buneman, P., and Suciu, D. (1999). Data on the Web: From Relations to Semistructured Data and XML. Morgan Kaufmann.Google Scholar
  11. Abiteboul, S., Manolescu, I., Rigaux, P., Rousset, M.-C., and Senellart, P. (2011). Web Data Management. Cambridge University Press.CrossRefGoogle Scholar
  12. Abou-Rjeili, A. and Karypis, G. (2006). Multilevel algorithms for partitioning power-law graphs. In Proc. 20th IEEE Int. Parallel & Distributed Processing Symp., pages 124–124.Google Scholar
  13. Abouzeid, A., Bajda-Pawlikowski, K., Abadi, D., Silberschatz, A., and Rasin, A. (2009). HadoopDB: an architectural hybrid of MapReduce and DBMS technologies for analytical workloads. Proc. VLDB Endowment, 2 (1): 922–933.CrossRefGoogle Scholar
  14. Adali, S., Candan, K. S., Papakonstantinou, Y., and Subrahmanian, V. S. (1996a). Query caching and optimization in distributed mediator systems. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 137–148.Google Scholar
  15. Adali, S., Candan, K. S., Papakonstantinou, Y., and Subrahmanian, V. S. (1996b). Query caching and optimization in distributed mediator systems. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 137–148.Google Scholar
  16. Adamic, L. and Huberman, B. (2000). The nature of markets in the world wide web. Quart. J. Electron. Comm., 1: 5–12.Google Scholar
  17. Adiba, M. (1981). Derived relations: A unified mechanism for views, snapshots and distributed data. In Proc. 7th Int. Conf. on Very Data Bases, pages 293–305.Google Scholar
  18. Adiba, M. and Lindsay, B. (1980). Database snapshots. In Proc. 6th Int. Conf. on Very Data Bases, pages 86–91.Google Scholar
  19. Adler, M. and Mitzenmacher, M. (2001). Towards compressing web graphs. In Proc. Data Compression Conf., pages 203–212.Google Scholar
  20. Aggarwal, C. C., editor. (2007). Data Streams: Models and Algorithms. Springer.Google Scholar
  21. Agichtein, E., Lawrence, S., and Gravano, L. (2004). Learning to find answers to questions on the web. ACM Trans. Internet Tech., 4 (3): 129—162.CrossRefGoogle Scholar
  22. Agrawal, D. and Sengupta, S. (1993). Modular synchronization in distributed, multiversion databases: Version control and concurrency control. IEEE Trans. Knowl. and Data Eng., 5 (1): 126 –137.CrossRefGoogle Scholar
  23. Agrawal, D., Das, S., and El Abbadi, A. (2012). Data Management in the Cloud: Challenges and Opportunities. Synthesis Lectures on Data Management. Morgan & Claypool Publishers.Google Scholar
  24. Agrawal, S., Narasayya, V., and Yang, B. (2004). Integrating vertical and horizontal partitioning into automated physical database design. In Proc. ACM SIGMOD Int. Conf. on Management of Data.Google Scholar
  25. Akal, F., Böhm, K., and Schek, H.-J. (2002). Olap query evaluation in a database cluster: A performance study on intra-query parallelism. In Proc. 6th East European Conf. Advances in Databases and Information Systems, pages 218–231.Google Scholar
  26. Akal, F., Türker, C., Schek, H.-J., Breitbart, Y., Grabs, T., and Veen, L. (2005). Fine-grained replication and scheduling with freshness and correctness guarantees. In Proc. 31st Int. Conf. on Very Large Data Bases, pages 565–576.Google Scholar
  27. Akbarinia, R. and Martins, V. (2007). Data management in the APPA system. J. Grid Comp., 5 (3): 303–317.CrossRefGoogle Scholar
  28. Akbarinia, R., Martins, V., Pacitti, E., and Valduriez, P. (2006). Design and implementation of Atlas P2P architecture. In Baldoni, R., Cortese, G., and Davide, F., editors, Global Data Management, pages 98–123. IOS Press.Google Scholar
  29. Akbarinia, R., Pacitti, E., and Valduriez, P. (2007a). Processing top-k queries in distributed hash tables. In Proc. 13th Int. Euro-Par Conf., pages 489–502.Google Scholar
  30. Akbarinia, R., Pacitti, E., and Valduriez, P. (2007b). Query processing in P2P systems. Technical Report 6112, INRIA, Rennes, France.Google Scholar
  31. Akbarinia, R., Pacitti, E., and Valduriez, P. (2007c). Best position algorithms for top-k queries. In Proc. 33rd Int. Conf. on Very Large Data Bases, pages 495–506.Google Scholar
  32. Akbarinia, R., Pacitti, E., and Valduriez, P. (2007d). Data currency in replicated dhts. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 211–222.Google Scholar
  33. Akidau, T., Balikov, A., Bekiroglu, K., Chernyak, S., Haberman, J., Lax, R., McVeety, S., Mills, D., Nordstrom, P., and Whittle, S. (2013). MillWheel: Fault-tolerant stream processing at internet scale. Proc. VLDB Endowment, 6 (11): 1033–1044.CrossRefGoogle Scholar
  34. Alagiannis, I., Borovica, R., Branco, M., Idreos, S., and Ailamaki, A. (2012). NoDB: efficient query execution on raw data files. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 241–252.Google Scholar
  35. Alagiannis, I., Idreos, S., and Ailamaki, A. (2014). H2O: A hands-free adaptive store. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 1103–1114.Google Scholar
  36. Alamoudi, A. A., Grover, R., Carey, M. J., and Borkar, V. R. (2015). External data access and indexing in AsterixDB. In Proc. 24th ACM Int. Conf. on Information and Knowledge Management, pages 3–12.Google Scholar
  37. Albutiu, M.-C., Kemper, A., and Neumann, T. (2012). Massively parallel sort-merge joins in main memory multi-core database systems. Proc. VLDB Endowment, 5 (10): 1064–1075.CrossRefGoogle Scholar
  38. Allard, T., Hébrail, G., Masseglia, F., and Pacitti, E. (2015). Chiaroscuro: Transparency and privacy for massive personal time-series clustering. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 779–794.Google Scholar
  39. Alomari, M., Cahill, M., Fekete, A., and Rohm, U. (2008). The cost of serializability on platforms that use snapshot isolation. In Proc. 24th Int. Conf. on Data Engineering, pages 576 –585.Google Scholar
  40. Alomari, M., Fekete, A., and Rohm, U. (2009). A robust technique to ensure serializable executions with snapshot isolation DBMS. In Proc. 25th Int. Conf. on Data Engineering, pages 341–352.Google Scholar
  41. Alsberg, P. A. and Day, J. D. (1976). A principle for resilient sharing of distributed resources. In Proc. 2nd Int. Conf. on Software Engineering, pages 562–570.Google Scholar
  42. Alsubaiee, S., Altowim, Y., Altwaijry, H., Behm, A., Borkar, V. R., Bu, Y., Carey, M. J., Cetindil, I., Cheelangi, M., Faraaz, K., Gabrielova, E., Grover, R., Heilbron, Z., Kim, Y., Li, C., Li, G., Ok, J. M., Onose, N., Pirzadeh, P., Tsotras, V. J., Vernica, R., Wen, J., and Westmann, T. (2014). AsterixDB: A scalable, open source DBMS. Proc. VLDB Endowment, 7 (14): 1905–1916.CrossRefGoogle Scholar
  43. Altingövde, I. S. and Ulusoy, Ö. (2004). Exploiting interclass rules for focused crawling. IEEE Intelligent Systems, 19 (6): 66–73.CrossRefGoogle Scholar
  44. Aluç, G. (2015). Workload Matters: A Robust Approach to Physical RDF Database Design. PhD thesis, University of Waterloo.Google Scholar
  45. Alvarez, V., Schuhknecht, F. M., Dittrich, J., and Richter, S. (2014). Main memory adaptive indexing for multi-core systems. In Proc. 10th Workshop on Data Management on New Hardware, pages 3:1—-3:10.Google Scholar
  46. Amdahl, G. M. (1967). Validity of the single processor approach to achieving large scale computing capabilities. In Proc. Spring Joint Computer Conf., pages 483–485.Google Scholar
  47. Amsaleg, L., Franklin, M. J., Tomasic, A., and Urhan, T. (1996). Scrambling query plans to cope with unexpected delays. In Proc. 4th Int. Conf. on Parallel and Distributed Information Systems, pages 208–219.Google Scholar
  48. Andreev, K. and Racke, H. (2006). Balanced graph partitioning. Theor. Comp. Sci., 39 (6): 929–939.MathSciNetzbMATHGoogle Scholar
  49. Angles, R. and Gutierrez, C. (2008). The expressive power of SPARQL. In Proc. 7th Int. Semantic Web Conf., pages 114–129.Google Scholar
  50. Antoniou, G. and Plexousakis, D. (2018). Semantic web. In Liu, L. and Özsu, M. T., editors, Encyclopedia of Database Systems, pages 3425–3429. Springer New York, New York, NY.CrossRefGoogle Scholar
  51. Apache. (2016). Apache Giraph. Last accessed June 2019.
  52. Apers, P., van den Berg, C., Flokstra, J., Grefen, P., Kersten, M., and Wilschut, A. (1992). Prisma/DB: a parallel main-memory relational DBMS. IEEE Trans. Knowl. and Data Eng., 4: 541–554.CrossRefGoogle Scholar
  53. Apers, P. M. G. (1981). Redundant allocation of relations in a communication network. In Proc. 5th Berkeley Workshop on Distributed Data Management and Computer Networks, pages 245–258.Google Scholar
  54. Arasu, A. and Widom, J. (2004). A denotational semantics for continuous queries over streams and relations. ACM SIGMOD Rec., 33 (3): 6–11.CrossRefGoogle Scholar
  55. Arasu, A., Cho, J., Garcia-Molina, H., Paepcke, A., and Raghavan, S. (2001). Searching the web. ACM Trans. Internet Tech., 1 (1): 2–43.CrossRefGoogle Scholar
  56. Arasu, A., Babu, S., and Widom, J. (2006). The CQL continuous query language: Semantic foundations and query execution. VLDB J., 15 (2): 121–142.CrossRefGoogle Scholar
  57. Armbrust, M., Xin, R. S., Lian, C., Huai, Y., Liu, D., Bradley, J. K., Meng, X., Kaftan, T., Franklin, M. J., Ghodsi, A., and Zaharia, M. (2015). Spark SQL: Relational data processing in Spark. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 1383–1394.Google Scholar
  58. Arocena, G. and Mendelzon, A. (1998). WebOQL: Restructuring documents, databases and webs. In Proc. 14th Int. Conf. on Data Engineering, pages 24–33.Google Scholar
  59. Asad, O. and Kemme, B. (2016). Adaptcache: Adaptive data partitioning and migration for distributed object caches. In Proc. ACM/IFIP/USENIX 17th Int. Middleware Conf., pages 7:1–7:13.Google Scholar
  60. Aspnes, J. and Shah, G. (2003). Skip graphs. In Proc. 14th Annual ACM-SIAM Symp. on Discrete Algorithms, pages 384–393.Google Scholar
  61. Avnur, R. and Hellerstein, J. (2000). Eddies: Continuously adaptive query processing. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 261–272.Google Scholar
  62. Ayad, A. and Naughton, J. (2004). Static optimization of conjunctive queries with sliding windows over unbounded streaming information sources. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 419–430.Google Scholar
  63. Azar, Y., Broder, A. Z., Karlin, A. R., and Upfal, E. (1999). Balanced allocations. SIAM J. on Comput., 29 (1): 180–200.MathSciNetzbMATHCrossRefGoogle Scholar
  64. Babb, E. (1979). Implementing a relational database by means of specialized hardware. ACM Trans. Database Syst., 4 (1): 1–29.CrossRefGoogle Scholar
  65. Babcock, B., Babu, S., Datar, M., Motwani, R., and Widom, J. (2002). Models and issues in data stream systems. In Proc. ACM SIGACT-SIGMOD Symp. on Principles of Database Systems, pages 1–16.Google Scholar
  66. Balazinska, M., Kwon, Y., Kuchta, N., and Lee, D. (2007). Moirae: History-enhanced monitoring. In Proc. 3rd Biennial Conf. on Innovative Data Systems Research, pages 375–386.Google Scholar
  67. Balke, W.-T., Nejdl, W., Siberski, W., and Thaden, U. (2005). Progressive distributed top-k retrieval in peer-to-peer networks. In Proc. 21st Int. Conf. on Data Engineering, pages 174–185.Google Scholar
  68. Bancilhon, F. and Spyratos, N. (1981). Update semantics of relational views. ACM Trans. Database Syst., 6 (4): 557–575.zbMATHCrossRefGoogle Scholar
  69. Barbara, D., Garcia-Molina, H., and Spauster, A. (1986). Policies for dynamic vote reassignment. In Proc. 6th IEEE Int. Conf. on Distributed Computing Systems, pages 37–44.Google Scholar
  70. Barbara, D., Molina, H. G., and Spauster, A. (1989). Increasing availability under mutual exclusion constraints with dynamic voting reassignment. ACM Trans. Comp. Syst., 7 (4): 394–426.CrossRefGoogle Scholar
  71. Barthels, C., Loesing, S., Alonso, G., and Kossmann, D. (2015). Rack-scale in-memory join processing using RDMA. In Proc. ACM SIGMOD Int. Conf. on Management of Data, pages 1463–1475.Google Scholar
  72. Batini, C. and Lenzirini, M. (1984). A methodology for data schema integration in entity-relationship model. IEEE Trans. Softw. Eng., SE-10 (6): 650–654.CrossRefGoogle Scholar
  73. Batini, C., Lenzirini, M., and Navathe, S. B. (1986). A comparative analysis of methodologies for database schema integration. ACM Comput. Surv., 18 (4): 323–364.CrossRefGoogle Scholar
  74. Beeri, C., Bernstein, P. A., and Goodman, N. (1989). A model for concurrency in nested transaction systems. J. ACM, 36 (2): 230–269.MathSciNetzbMATHCrossRefGoogle Scholar
  75. Bell, D. and Grimson, J. (1992). Distributed Database Systems. Addison Wesley. Reading.zbMATHGoogle Scholar
  76. Bell, D. and Lapuda, L. (1976). Secure computer systems: Unified exposition and Multics interpretation. Technical Report MTR-2997 Rev.1, MITRE Corp, Bedford, MA.Google Scholar

Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  • M. Tamer Özsu
    • 1
  • Patrick Valduriez
    • 2
  1. 1.Cheriton School of Computer ScienceUniversity of WaterlooWaterlooCanada
  2. 2.Inria and LIRMMUniversity of MontpellierMontpellierFrance

Personalised recommendations