Big data storage

New Horizons for a Data-Driven Economy: A Roadmap for Usage and Exploitation of Big Data in Europe

Volumn , Issue , 2016, Pages 119-141

  Strohbach, Martin ^a   Daubert, Jörg ^a   Ravkin, Herman ^b   Lischka, Mario ^c  

^a AGT Group (RandD) GmbH   (Germany)

^b TEL AVIV UNIVERSITY   (Israel)

^c acentrix GmbH   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 85018705502     PISSN: None     EISSN: None     Source Type: Book    
DOI: 10.1007/978-3-319-21569-3_7     Document Type: Chapter

References (67)

1. Acquisti, A., & Gross, R. (2009). Predicting social security numbers from public data. Proceedings of the National Academy of Sciences, 106(27), 10975-10980.
2. Ahmadi Zeleti, F., Ojo, A., & Curry, E. (2014). Business models for the open data industry: Characterization and analysis of emerging models. In 15th Annual International Conference on Digital Government Research (dg.o 2014) (pp. 215-226). ACM.
3. Apache. (2014). Apache HBase Project Website. http://hbase.apache.org. Accessed Nov 21, 2014.
4. Aranda, C. B., Corby, O., Das, S., Feigenbaum, L., Gearon, P., Glimm, B., et al. (2013). SPARQL 1.1 overview. In W3C Recommendation.
5. Baeza-Yates, R. (2013). BIG Interview by John Dominque.
6. Blaze, M., Bleumer, G., & Strauss, M. (2006). Divertible protocols and atomic proxy cryptography. In Proceedings of Eurocrypt (pp. 127-144).
7. Blueprints. (2014). Blueprints Project Homepage. https://github.com/tinkerpop/blueprints/wiki. Accessed Feb 4, 2015.
8. Bollier, D., & Firestone, C. M. (2010). The promise and peril of big data. Washington, DC: Aspen Institute, Communications and Society Program.
9. Calder, B., Wang, J., Ogus, A., Nilakantan, N., Skjolvsvold, A., McKelvie, S. et al. (2011). Windows azure storage: a highly available cloud storage service with strong consistency. In: Proceedings of the Twenty-Third ACM Symposium on Operating Systems Principles (143-157). New York, NY: ACM.
10. CloudDrive. (2013). Advantages of cloud data storage. http://www.clouddrive.com.au/download/ www.clouddrive.com.au-WhitePaper.pdf. Accessed Nov 20, 2013.
11. Cloudera. (2012). Treato Customer Case Study. https://www.cloudera.com/content/dam/cloudera/ Resources/PDF/casestudy/Cloudera_Customer_Treato_Case_Study.pdf
12. Cloudera. (2013). Identifying fraud, managing risk and improving compliance in financial services.
13. Cloudera. (2014a). Cloudera Company Web page. www.cloudera.com. Accessed May 6, 2015.
14. Cloudera. (2014b). Rethink data. http://www.cloudera.com/content/cloudera/en/new/. Accessed Feb 4, 2014.
15. Curry, E., Ngonga, A., Domingue, J., Freitas, A., Strohbach, M., Becker, T., et al. (2014). D2.2.2. Final version of the technical white paper. Public deliverable of the EU-Project BIG (318062; ICT-2011.4.4).
16. DeBrabant, J., Pavlo, A., Tu, S., Stonebraker, M., & Zdonik, S. (2013). Anti-caching: a new approach to database management system architecture. In Proceedings of the VLDB Endowment (pp 1942-1953).
17. Erling, O. (2009). Virtuoso, a Hybrid RDBMS/Graph Column Store. In: Virtuoso Open-Source Wiki. http://virtuoso.openlinksw.com/dataspace/doc/dav/wiki/Main/ VOSArticleVirtuosoAHybridRDBMSGraphColumnStore. Accessed Feb 6, 2015.
18. Franz. (2015). Allegrograph product web page. http://franz.com/agraph/allegrograph/. Accessed Feb 6, 2015.
19. Gislason, H. (2013). BIG Interview by John Dominque.
20. Glavic, B. (2014). Big data provenance: Challenges and implications for benchmarking. In T. Rabl, M. Poess, C. Baru, & H.-A. Jacobsen (Eds.), Specifying big data benchmarks (pp. 72-80). Berlin: Springer.
21. Goyal, V., Pandey, O., Sahai, A., & Waters, B. (2006). Attribute-based encryption for fine-grained access control of encrypted data. In Proceedings of the 13th ACM Conference on Computer and Communications Security (pp. 89-98).
22. Grady, J. (2013). Is enterprise cloud storage a good fit for your business? http://www.1cloudroad. com/is-enterprise-cloud-storage-a-good-fit-for-your-business
23. Harizopoulos, S., Abadi, D. J., Madden, S., & Stonebraker, M. (2008). OLTP through the looking glass, and what we found there. In Proceedings of the 2008 ACM SIGMOD International Conference on Management data (SIGMOD '08).
24. Hasan, O., Habegger, B., Brunie, L., Bennani, N., & Damiani, E. (2013). A discussion of privacy challenges in user profiling with big data techniques: The EEXCESS use case. IEEE International Congress on Big Data (pp. 25-30).
25. Hortonworks. (2014). Hortonworks Company Web Page. http://hortonworks.com/. Accessed Feb 6, 2015.
26. Ikeda, R., Park, H., & Widom, J. (2011). Provenance for generalized map and reduce workflows. In Biennial Conference on Innovative. Data Systems Research (pp. 273-283).
27. iQuartic. (2014). iQuartic pioneers use of Hadoop with Electronic Health Records (EHRs/EMRs). In: iQuartic Blog. http://www.iquartic.com/blog/. Accessed Feb 7, 2014.
28. Kamara, S., & Lauter, K. (2010). Cryptographic cloud storage. In Financial Cryptography and Data Security (pp. 136-149).
29. Kobielus, J. (2013) Big Data needs data virtualization. In: InfoWorld Webpage. http://www. infoworld.com/article/2611579/big-data/big-data-needs-data-virtualization.html. Accessed Nov 18, 2014.
30. Koomey, J. G. (2008). Worldwide electricity used in data centers. Environmental Research Letters, 3, 034008. doi:10.1088/1748-9326/3/3/034008.
31. Lee, C.-C., Chung, P.-S., & Hwang, M.-S. (2013). A survey on attribute-based encryption schemes of access. International Journal of Network Security, 15, 231-240.
32. Lee, K., Manning, S., Melton, J., Boyd, D., Grady, N., & Levin, O. (2014). Final SGBD report to JTC1, ISO/IEC JTC1 SGBD document no. N0095.
33. Li, M., Yu, S., Zheng, Y., Ren, K., Lou, W., et al. (2013). Scalable and secure sharing of personal health records in cloud computing using attribute-based encryption. IEEE Transactions on Parallel and Distributed Systems, 24, 131-143.
34. Lobillo, F., Puente, M. A., Lippell, H., Zillner, S., Bretschneider, C., Oberkampf, H., et al. (2013). BIG deliverable D2.4.1 - First draft of sector's roadmaps.
35. Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., et al. (2011). Big data: The next frontier for innovation, competition, and productivity. Sydney: McKinsey Global Institute. http://www.mckinsey.com/insights/business_technology/big_data_the_next_fron tier_for_innovation.
36. MapR. (2014). MapR Company Website. https://www.mapr.com/. Accessed Feb 6, 2014.
37. Margaret Rouse. (2014a). Object Storage. http://searchstorage.techtarget.com/definition/objectstorage. Accessed Nov 20, 2014.
38. Margaret Rouse. (2014b). Block Storage. http://searchstorage.techtarget.com/definition/block-stor age. Accessed Feb 4, 2014.
39. Marz, N., & Warren, J. (2014). A new paradigm for Big Data. In N. Marz & J. Warren (Eds.), Big Data: Principles and best practices of scalable real-time data systems. Shelter Island, NY: Manning Publications.
40. Melnik, S., Garcia-Molina, H., & Rahm, E. (2002). Similarity flooding: A versatile graph matching algorithm and its application to schema matching. In Proceedings of the 18th International Conference Data Engineering. IEEE Computer Society (pp. 117-128).
41. Miller, S. P., Neuman, B. C., Schiller, J. I., & Saltzer, J. H. (1987, December 21). Section E.2.1: Kerberos authentication and authorization system. MIT Project Athena, Cambridge, MA.
42. Mora, A. C., Chen, Y., Fuchs, A., Lane, A., Lu, R., Manadhata, P. et al. (2012). Top Ten Big Data Security and Privacy Challenges. Cloud Security Alliance (CSA).
43. Neo4j. (2015). Neo4j Company Website. http://neo4j.com/. Accessed Feb 6, 2015.
44. Okman, L., Gal-Oz, N., Gonen, Y., et al. (2011). Security issues in nosql databases. In 2011 I.E. 10th International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom) (pp. 541-547).
45. OpenStack. (2014). OpenStack Website. http://www.openstack.org. Accessed Feb 3, 2014.
46. PEC. (2014). Peer Energy Cloud Project Website. http://www.peerenergycloud.de/. Accessed Feb 6, 2015.
47. Russel, J. (2013). Cloudera Impala. O#Reilly Media
48. Shenker, S., Stoica, I., Zaharia, M., & Xin, R. (2013). Shark: SQL and rich analytics at scale. In Proceedings of the 2013 ACM SIGMOD International Conference on Management of Data (pp. 13-24).
49. Sherif, A., Sohan, R., & Hopper, A. (2013). HadoopProv: Towards provenance as a first class citizen in MapReduce. In Proceedings of the 5th USENIX Workshop on the Theory and Practice of Provenance.
50. Shucheng, Y., Wang, C., Ren, K., & Lou, W. (2010). Achieving secure, scalable, and fine-grained data access control in cloud computing. INFOCOM (pp. 1-9).
51. Shvachko, K. H. K., Radia, S., & Chansler, R. (2010). The Hadoop distributed file system. In IEEE 26th Symposium on Mass Storage Systems and Technologies (pp. 1-10).
52. Stonebraker, M. (2012a) What Does "Big Data" Mean? In: BLOG@ACM. http://cacm.acm.org/ blogs/blog-cacm/155468-what-does-big-data-mean/fulltext. Accessed Feb 5, 2015.
53. Stonebraker, M. (2012b). What Does "Big Data" Mean? (Part 2). In: BLOG@ACM. http://cacm. acm.org/blogs/blog-cacm/156102-what-does-big-data-mean-part-2/fulltext. Accessed Apr 25, 2013.
54. Strohbach, M., Ziekow, H., Gazis, V., & Akiva, N. (2011). Towards a big data analytics framework for IoT and smart city applications. In F. Xhafa & P. Papajorgji (Eds.), Modeling and processing for next generation big data technologies with applications (pp. 257-282). Berlin: Springer.
55. Thusoo, A., Sarma, J., Jain, N., Shao, Z., Chakka, P., Anthony, S., et al. (2009). Hive - a warehousing solution over a map-reduce framework. Statistics and Operations Research Transactions, 2, 1626-1629.
56. Turner, V., Gantz, J. F., Reinsel, D., & Minton, S. (2014). The digital universe of opportunities: Rich data and the increasing value of the internet of things. Framingham, MA: International Data Corporation (IDC). http://idcdocserv.com/1678. Accessed Aug 19, 2015.
57. Venkatesh, P., & Nirmala, S. (2012). NewSQL - The new way to handle big data. In: Blog. http:// www.opensourceforu.com/2012/01/newsql-handle-big-data/. Accessed Nov 18, 2014.
58. Vogels, W. (2013). Day 2 Keynote. AWS reInvent.
59. VoltDB. (2014). VoltDB Company Website. http://www.voltdb.com. Accessed Nov 21, 2014.
60. Webber, J. (2013). BIG Interview by John Dominque.
61. White, T. (2012). Hadoop: The Definitive Guide. O'Reilly.
62. Wikipedia. (2013). Column-oriented DBMS. http://en.wikipedia.org/wiki/Column-oriented_ DBMS. Accessed Apr 25, 2013.
63. Winder, D. (2012). Securing NoSQL applications: Best practises for big data security. Computer Weekly.
64. Wu, C., & Guo, Y. (2013). Enhanced user data privacy with pay-by-data model. In Proceeding of 2013 I.E. International Conference on Big Data (pp. 53-57).
65. Zaharia, M., Chowdhury, M., Franklin, M. J., Shenker, S., & Stoica, I. (2010). Spark: Cluster computing with working sets. In HotCloud'10 Proceedings of the 2nd USENIX Conference on Hot Topics in Cloud Computing (p. 10).
66. Ziekow, H., Goebel, C., Struker, J., & Jacobsen, H.-A. (2013). The potential of smart home sensors in forecasting household electricity demand. In Smart Grid Communications (SmartGridComm), 2013 I.E. International Conferences (pp. 229-234).
67. Zillner, S., Neururer, S., Munne, R., Prieto, E., Strohbach, M., van Kasteren, T., et al. (2014). D2.3.2. Final Version of the Sectorial Requisites. Public Deliverable of the EU-Project BIG (318062; ICT-2011.4.4).