Дополнение A. Ссылки

[1] Avi Silberschatz, Peter Baer and Galvin Greg Gagne, Operating System Concepts, 10th ed., John Wiley & Sons, 2013, p. 10.

[2] David A. Patterson and John L.Hennessy, Computer Organization and Design. The hardware/software interface, 5th ed., Elsevier, 2014, p. 378.

[3] B. Lincoln, Digital Electronics, 1/e, Pearson India, 2014.

[4] ITL Limited ITL Education Solutions Limited, Introduction to Computer Science, Pearson Education India, 2011.

[5] A. N. Kamthane and R. Kamal, Computer Programming and IT, Pearson India, 2012.

[6] J. S. Warford, Computer systems, 5th ed., Jones & Bartlett Learning, 2016.

[7] S. Haldar and A. Aravind, Operating Systems, Pearson India, 2009.

[8] R. Sedgewick and K. Wayne, Computer Science: An Interdisciplinary Approach, Addison-Wesley Professional, 2016.

[9] R. e. O’Neill, Learning Linux Binary Analysis, 2016.

[10] Oracle, "Locality Groups Overview," 28 09 2017. [Online].

[11] M. K. McKusick, G. V. Neville-Neil and R. N. Watson, "The Slab Allocator," in The Design and Implementation of the FreeBSD Operating System,2nd ed., Addison-Wesley Professional, 2014.

[12] E. C. Foster and S. V. Godbole, Database Systems, Apress, 2014.

[13] J. G. Raghu Ramakrishnan, Database Management Systems, 3th ed., McGraw-Hill, 2002.

[14] S. Naik, Concepts of Database Management System, Pearson India, 2013.

[15] G. S. M. Calzarossa, "Workload characterization: a survey," Proceedings of the IEEE ( Volume: 81, Issue: 8, Aug 1993 ), pp. 1136 - 1150, 1993.

[16] H. Garcia-Molina, J.Ullman, J.Widom, Database Systems: The complete Book, Second Edition, New Jersey: Prentice Hall, 2009.

[17] R. A. Steward and J. Goodson, The Data Access Handbook: Achieving Optimal Database Application Performance and Scalability, Prentice Hall, 2009.

[18] D. Vadala, Managing RAID on Linux, O’Reilly Media, Inc, 2002.

[19] Oracle Corporation, MySQL 5.7 Reference Manual, Oracle Corporation, 2018.

[20] S. Pachev, Understanding MySQL Internals, O’Reilly Media, Inc, 2007.

[21] H. Zhang, G. Chen, B. Chin Ooi, K. Tan, M. Zhang, "In-Memory Big Data Management and Processing: A Survey", IEEE Transactions on Knowledge and Data Engineering, ( Volume: 27, Issue: 7, July 1 2015 ) .

[22] Gianlucca O.Puglia, Avelino F.Zorzo, Cesar A.F. de Rose, Taciano D.Perez, and Dejan Milojicic, "Non-Volatile Memory File Systems: A Survey". IEEE Access, Vol. 7, 2019.

[23] V. Sikka, F. Farber, A. Goel, and W. Lehner, “SAP HANA: The evolution from a modern main-memory data platform to an enterprise application platform", Proc. VLDB Endowment, vol. 6, pp. 1184–1185, 2013.

[24] M. Stonebraker and A. Weisberg, “The voltDB main memory DBMs,” IEEE Data Eng. Bull., vol. 36, no. 2, Jun. 2013.

[25] T. Lahiri, M.-A. Neimat, and S. Folkman, “Oracle timesten: An in-memory database for enterprise applications,” IEEE Data Eng. Bull., vol. 36, no. 2, pp. 6–13, Jun. 2013.

[26] J. Lindström, V. Raatikka, J. Ruuth, P. Soini, and K. Vakkila, “IBM solidDB: In-memory database optimized for extreme speed and availability,” IEEE Data Eng. Bull., vol. 36, no. 2, pp. 14–20, Jun. 2013.

[27] V. Raman, G. Attaluri, R. Barber, N. Chainani, D. Kalmuk, V. KulandaiSamy, J. Leenstra, S. Lightstone, S. Liu, G. M. Lohman, T. Malkemus, R. Mueller, I. Pandis, B. Schiefer, D. Sharpe, R. Sidle, A. Storm and L.Zhang, “DB2 with BLU acceleration: So much more than just a column store” Proc. VLDB Endowment, vol. 6, pp. 1080–1091, 2013.

[28] C. Diaconu, C. Freedman, E. Ismert, P.-A. Larson, P. Mittal, R. Stonecipher, N. Verma, and M. Zwilling, “Hekaton: SQL server’s memory-optimized OLTP engine,” in Proc. ACM SIGMOD Int. Conf. Manag. Data, 2013, pp. 1243–1254.

[29] R. Kallman, H. Kimura, J. Natkins, A. Pavlo, A. Rasin, S. Zdonik, E. P. C. Jones, S. Madden, M. Stonebraker, Y. Zhang, J. Hugg, and D. J. Abadi, “H-store: A high-performance, distributed main memory transaction processing system,” Proc. VLDB Endowment, vol. 1, pp. 1496–1499, 2008.

[30] B. Brynko, “Nuodb: Reinventing the database,” Inf. Today, vol. 29, no. 9, p.9, 2012.

[31] McObject, “extremedb database system,” 2001. [Online]. Available: http://www.mcobject.com/extremedbfamily.shtml

[32] Pivotal. (2013). Pivotal SQLFire [Online]. Available: http://www.vmware.com/products/vfabric-sqlfre/overview.html

[33] MemSQL Inc. (2012). Memsql [Online]. Available: http://www.memsql.com/

[34] FoundationDB. (2013). Foundationdb[Online]. Available: https://foundationdb.com [35] A. Kemper and T. Neumann, “HyPer: A hybrid OLTP & OLAP main memory database system based on virtual memory snapshots,” in IEEE 27th Int. Conf. Data Eng., 2011, pp. 195–206.

[36] S. Tu, W. Zheng, E. Kohler, B. Liskov, and S. Madden, “Speedy transactions in multicore in-memory databases,” in Proc. ACM Symp. Operating Syst. Principles, 2013, pp. 18–32.

[37] P. Unterbrunner, G. Giannikis, G. Alonso, D. Fauser, and D. Kossmann, “Predictable performance for unpredictable workloads,” Proc. VLDB Endowment, vol. 2, pp. 706–717, 2009.

[38] M. Grund, J. Krüger, H. Plattner, A. Zeier, P. Cudre-Mauroux, and S. Madden, “HYRISE: A main memory hybrid storage engine,” Proc. VLDB Endowment, vol. 4, pp. 105–116, 2010.

[39] Oracle. (2004). MySQL cluster NDB [Online]. Available: http://www.mysql.com/

[40] A. Eldawy, J. J. Levandoski, and P. Larson, “Trekking through Siberia: Managing cold data in a memory-optimized database,” in Proc. Int. Conf. Very Large Data Bases, 2014, pp. 931–942.

[41] T. Mühlbauer, W. Rödiger, A. Reiser, A. Kemper, and T. Neumann, “ScyPer: Elastic OLAP throughput on transactional data,” in Proc. 2nd Workshop Data Analytics Cloud, 2013, pp. 11–15.

[42] A. Kemper and T. Neumann, “HyPer: A hybrid OLTP & OLAP main memory database system based on virtual memory snapshots,” in IEEE 27th Int. Conf. Data Eng., 2011, pp. 195–206.

[43] A. Kemper and T. Neumann, “One size fts all, again! the architecture of the hybrid oltp & olap database management system hyper,” in Proc. 4th Int. Workshop Enabling Real-Time Bus. Intell., 2010, pp. 7–23.

[44] H. Mühe, A. Kemper, and T. Neumann, “How to efciently snapshot transactional data: Hardware or software controlled?” in Proc. 7th Int. Workshop DataManag. New Hardware, 2011, pp. 17–26.

[45] T. Neumann, “Efciently compiling efcient query plans for modern hardware,” Proc. VLDB Endowment, vol. 4, pp. 539–550, 2011.

[46] V. Leis, A. Kemper, and T. Neumann, “The adaptive radix tree: ARTfulindexing for main-memory databases,” in Proc. IEEE 29th Int. Conf. Data Eng.,2013, pp. 38–49.

[47] H. Plattner, “A common database approach for OLTP and olap USING an in-memory column database,” in Proc. ACM SIGMOD Int. Conf. Manag. Data,2009, pp. 1–2.

[48] M. Kaufmann and D. Kossmann, “Storing and processing temporal data in a main memory column store,” Proc. VLDB Endowment, vol. 6, pp. 1444–1449, 2013.

[49] Intel® 64 and IA-32 Architectures Software Developer’s Manual Volume 3A: System Programming Guide, Part 1. https://www.intel.es/content/www/es/es/architecture-and-technology/64-ia-32-architectures-software-developer-vol-3a-part-1-manual.html

[50] AMD64 Architecture, Programmer’s Manual, Volume 2: System Programming, https://www.amd.com/system/fles/TechDocs/24593.pdf

[51] F. Chang, J. Dean, S. Ghemawat, W. C. Hsieh, D. A. Wallach, M. Burrows, T. Chandra, A. Fikes, and R. E. Gruber, “Bigtable: A distributed storage system for structured data,” ACM Trans. Compu. Syst., vol. 26, pp. 4:1–4:26, 2008.

[52] S. Sanflippo and P. Noordhuis. (2009). Redis [Online]. Available: http://redis.io

[53] J. Ousterhout, P. Agrawal, D. Erickson, C. Kozyrakis, J. Leverich, D. Mazieres, S. Mitra, A. Narayanan, G. Parulkar, M. Rosenblum, S. M. Rumble, E. Stratmann, and R. Stutsman, “The case for RAMClouds: Scalable high performance storage entirely in dram,” ACM SIGOPS Operating Syst. Rev., vol. 43, pp. 92–105, 2010.

[54] Q. Cai, H. Zhang, G. Chen, B. C. Ooi, and K.-L. Tan, “Memepic: Towardsa database system architecture without system calls,” NUS, 2014.

[55] S. Ramachandran. (2013). Bitsy graph database [Online]. Available: https://bitbucket.org/lambdazen/bitsy

[56] MongoDB Inc. (2009). Mongodb [Online]. Available: http://www.mongodb.org

[57] M. C. Brown, Getting Started with Couchbase Server. Sebastopol, CA, USA: O’Reilly Media, 2012.

[58] B. Shao, H. Wang, and Y. Li, “Trinity: A distributed graph engine on a memory cloud,” in Proc. ACM SIGMOD Int. Conf. Manag. Data, 2013, pp. 505–516.

[59] S. Ramachandran. (2013). Bitsy graph database [Online]. Available: https://bitbucket.org/lambdazen/bitsy

[60] B. Bishop, A. Kiryakov, D. Ognyanof, I. Peikov, Z. Tashev, and R. Velkov, “OWLIM: A family of scalable semantic repositories,” Semantic Web, vol. 2, pp. 33–42, 2011.

[61] WhiteDB Team. (2013). Whitedb [Online]. Available: http://whitedb.org

[62] P. A. Boncz, M. Zukowski, and N. Nes, “Monetdb/x100: Hyperpipelining query execution,” in Proc. CIDR, 2005, pp. 225–237.

[63] H. Chu, “MDB: A memory-mapped database and backend for openldap,” in Proc. LDAPCon, 2011.

[64] Hector Garcia-Molina, "Main Memory Database Systems: An Overview". IEEE Transactions on Knowledge and Data Engineering, Vol. 4, No. 6, December.

[65] F. Li, B. C. Ooi, M. T. Özsu, and S. Wu, “Distributed data management using MapReduce,” ACM Computing Surveys, vol. 46, pp. 31:1–31:42, 2014.