Abstract
Cloud computing has changed the way we used to exploit software and systems. The two decades’ practice of architecting solutions and services over the Internet has just revolved within the past few years. End users are now relying more on paying for what they use instead of purchasing a full-phase license. System owners are also in rapid hunt for business profits by deploying their services in the Cloud and thus maximising global outreach and minimising overall management costs. However, deploying and scaling Cloud applications regionally and globally are highly challenging. In this context, distributed data management systems in the Cloud promise rapid elasticity and horizontal scalability so that Cloud applications can sustain enormous growth in data volume, velocity, and value. Besides, distributed data replication and rapid partitioning are the two fundamental hammers to nail down these challenges. While replication ensures database read scalability and geo-reachability, data partitioning favours database write scalability and system-level load balance. System architects and administrators often face difficulties in managing a multi-tenant distributed database system in Cloud scale as the underlying workload characteristics change frequently. In this chapter, the inherent challenges of such phenomena are discussed in detail alongside their historical backgrounds. Finally, potential way outs to overcome such architectural barriers are presented under the light of recent research and development in this area.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Abadi DJ (April 2010) Problems with CAP, and Yahoo’s little known NoSQL system. http://dbmsmusings.blogspot.com.au/2010/04/problems-with-cap-and-yahoos-little.html. Accessed 31 Jan 2014
Abadi DJ (2012) Consistency tradeoffs in modern distributed database system design: CAP is only part of the story. Comput IEEE 45(2):37–42
Amazon DynamoDB—NoSQL Cloud Database Service (2014) http://aws.amazon.com/dynamodb. Accessed 31 Jan 2014
Apache Cassandra Project. http://cassandra.apache.org. Accessed 31 Jan 2014
Apache CouchDB. http://couchdb.apache.org. Accessed 31 Jan 2014
Apache HBase—Apache HBase Home. http://hbase.apache.org. Accessed 31 Jan 2014
Armbrust M, Fox A, Griffith R, Joseph AD, Katz RH, Konwinski A, Lee G, Paterson DA, Rabkin A, Stoica I, Zaharia M (2009) Above the clouds: a Berkeley view of cloud computing. Technical Report UCB/EECS-2009-28, EECS Department, University of California, Berkeley
Bernstein PA, Newcomer E (2009) Principles of transaction processing, 2nd edn. Morgan Kaufmann, San Francisco
Birman K, Freedman D, Huang Q, Dowell P (2012) Overcoming CAP with consistent soft-state replication. Comput IEEE 45(2):50–58
Brewer EA (2000) Towards robust distributed systems (abstract). In: Proceedings of the nineteenth annual ACM symposium on principles of distributed computing (New York, NY, USA, 2000), PODC’00, ACM, p. 7
Brewer E (2012) CAP twelve years later: how the “rules” have changed. Comput IEEE 45(2):23–29
Chang F, Dean J, Ghemawat S, Hsieh WC, Wallach DA, Burrows M, Chandra T, Fikes A, Gruber RE (2008) BigTable: a distributed storage system for structured data. ACM Trans Comput Syst 26(2), 4(1–4):26
Cooper BF, Ramakrishnan R, Srivastava U, Silberstein A, Bohannon P, Jacobsen H.-A, Puz N, Weaver D, Yerneni R (2008) PNUTS: Yahoo!’s hosted data serving platform. Proc VLDB Endow 1(2):1277–1288
Corbett JC, Dean J, Epstein M, Fikes A, Frost C, Furman JJ, Ghemawat S, Gubarev A, Heiser C, Hochschild P, Hsieh W, Kanthak S, Kogan E, Li H, Lloyd A, Melnik S, Mwaura D, Nagle D, Quinlan S, Rao R, Rolig L, Saito Y, Szymaniak M, Taylor C, Wang R, Woodford D (2012) Spanner: google’s globally distributed database. In: Proceedings of the 10th USENIX conference on operating systems design and implementation (Berkeley, CA, USA) OSDI’12, USENIX Association, pp 251–264
Floratou A, Teletia N, Dewitt DJ, Patel JM, Zhang D (2012) Can the elephants handle the NoSQL onslaught? Proc VLDB Endow 5(12):1712–1723
Gilbert S, Lynch N (June 2002) Brewer’s conjecture and the feasibility of consistent, available, partition-tolerant web services. SIGACT News 33(2):51–59
Gray J (1978) Notes on database operating systems. In: Gray J (ed) Operating systems, an advanced course. Springer-Verlag, London, pp 393–481
Gray J, Helland P, O’Neil P, Shasha D (1996) The dangers of replication and a solution. SIGMOD Rec 25(2):173–182
H-Store: Next Generation OLTP Database Research (2014) http://hstore.cs.brown.edu. ÂAccessed 31 Jan 2014
Jimenez-Peris R, Patino Martinez M, Kemme B, Perez-Sorrosal F, Serrano D (2009) A system of architectural patterns for scalable, consistent and highly available multi-tier service-oriented infrastructures. Architecting dependable systems VI. Springer-Verlag, Berlin, pp 1–23.
Kemme B (2000) Database replication for clusters of workstations. PhD thesis, Swiss Federal Institute of Technology, Zurich
Kemme B, Alonso G (2000) Don’t be lazy, be consistent: Postgres-R, a new way to implement database replication. In: Proceedings of the 26th international conference on very large data bases (San Francisco, CA, USA), VLDB ’00, Morgan Kaufmann Publishers Inc., pp 134–143
Kemme B, Alonso G (2000) A new approach to developing and implementing eager database replication protocols. ACM Trans Database Syst 25(3):333–379
Kemme B, Jimenez-Peris R, Pantino Martinez M, Salas J (2000) Exactly once interaction in a multi-tier architecture. In: VLDB workshop on design, implementation, and deployment of database replication
Kohana M, Okamoto S, Kamada M, Yonekura T (2010) Dynamic data allocation scheme for multi-server web-based MORPG system. In: Proceedings of the 2010 IEEE 24th international conference on advanced information networking and applications workshops (ÂWashington, DC, USA), WAINA ’10, IEEE Computer Society pp 449–454
Kohana M, Okamoto S, Kamada M, Yonekura T (2012) Dynamic reallocation rules on multi-server web-based MORPG system. Int J Grid Utility Comput 3(2/3):136–144
Lamport L (1998) The part-time parliament. ACM Trans Comput Syst 16(2):133–169
Lerner RM (2010) At the forge: NoSQL? I’d prefer some SQL. Linux J. 2010:192. (http://www.linuxjournal.com/article/10720. Accessed 31 Jan 2014)
Lindsay BG, Selinger PG, Galtieri CA, Gray JN, Lorie R A, Price TG, Putzulo F, Traiger IL, Wade BW (July 1979) Notes on distributed databases. Research Report, IBM Research Laboratory (San Jose, California, USA) 247–284
Miller RB (1968) Response time in man-computer conversational transactions. In: Proceedings of the December 9–11, 1968, fall joint computer conference, part I (New York, NY, USA), AFIPS ’68 (Fall, part I), ACM pp 267–277
MongoDB http://www.mongodb.org. Accessed 31 Jan 2014
MySQL MySQL Cluster CGE. http://www.mysql.com/products/cluster. Accessed 31 Jan 2014
Perez-Sorrosal F, Patino Martinez M, Jimenez-Peris R, Kemme B (2007) Consistent and scalable cache replication for multi-tier J2EE applications. In: Proceedings of the ACM/IFIP/USENIX 2007 international conference on Middleware (New York, NY, USA), Middleware ’07, Springer-Verlag New York, Inc., pp 328–347
Perez-Sorrosal F, Patino Martinez M, Jimenez-Pereis R, Kemme B (2007) Consistent and scalable cache replication for multi-tier J2EE applications. In: Proceedings of the 8th ACM/IFIP/USENIX international conference on Middleware (Berlin, Heidelberg), Middleware 2007 Springer-Verlag pp 328–347
Perez-Sorrosal F, Patino Martinez M, Jimenez-Peris R, Kemme B (2011) Elastic SI-Cache: consistent and scalable caching in multi-tier architectures. VLDB J 20(6):841–865
Prichett D (May 2008) BASE: an ACID alternative. Queue ACM 6(3):48–55
Ramakrishnan R (2012) CAP and Cloud data management. Computer IEEE 45(2): 43–49
Riak | Basho Technologies (2014) http://basho.com/riak. Accessed 31 Jan 2014
Schram A, Anderson KM (2012) MySQL to NoSQL: data modeling challenges in supporting scalability. In: Proceedings of the 3rd annual conference on systems, programming, and Âapplications: software for humanity (New York, NY, USA), SPLASH ’12, ACM, pp 191–202
Skeen D, Stonebraker M (1983) A formal model of crash recovery in a distributed system. Software engineering. IEEE Trans SE 9(3): 219–228
Stonebraker M (1986) The case for shared nothing. IEEE Database Eng Bull 9(1):4–9
Stonebraker M (4 Nov 2009) The “NoSQL” discussion has nothing to do with SQL. http://cacm.acm.org/blogs/blog-cacm/50678-the-nosql-discussion-has-nothing-to-do-with-sql/fulltext. Accessed 31 Jan 2014
Stonebraker M (5 April 2010) Errors in database systems, eventual consistency, and the cap theorem. Blog, Communications of the ACM
Stonebraker M (2010) SQL databases v. NoSQL databases. Commun ACM 53(4):10–11
Vogels W (Oct 2008) Eventually consistent. Queue ACM 6(6):14–19
Vogels W (2009) Eventually consistent. Communications of the ACM 52(1):40–44
VoltDB http://voltdb.com. Accessed 31 Jan 2014
Waldo J (2008) Scaling in games and virtual worlds. Commun ACM 51(8):38–44
Weinreb D Improving the PACELC taxonomy. http://danweinreb.org/blog/improving-the-pacelc-taxonomy. Accessed 27 Feb 2013
Wikipedia. Consensus (computer science). http://en.wikipedia.org/wiki/Consensus_(computer_science). Accessed 31 Jan 2014
Wikipedia. Paxos (computer science). http://en.wikipedia.org/wiki/Paxos_(computer_science). Accessed 31 Jan 2014
Zhang K, Kemme B, Denault A (2008) Persistence in massively multiplayer online games. In: Proceedings of the 7th ACM SIGCOMM workshop on network and system support for games (New York, NY, USA), NetGames’ 08, ACM, pp 53–58
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2014 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Kamal, J., Murshed, M. (2014). Distributed Database Management Systems: Architectural Design Choices for the Cloud. In: Mahmood, Z. (eds) Cloud Computing. Computer Communications and Networks. Springer, Cham. https://doi.org/10.1007/978-3-319-10530-7_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-10530-7_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-10529-1
Online ISBN: 978-3-319-10530-7
eBook Packages: Computer ScienceComputer Science (R0)