Fábio Roberto Oliveira
ABSTRACT
NoSQL data store systems have recently been introduced as alternatives to traditional relational database management systems. These data stores systems implement simpler and scalable data models that increase the performance and efficiency of a new kind of emerging complex database application. Applications that model their data using two or more simple NoSQL models are known as applications with polyglot persistence. Usually, their implementations are complex because they must manage and store their data using several data store systems simultaneously. Recently, a new family of multi-model data stores was introduced, integrating simple NoSQL data models into a single unique system. This paper presents a performance evaluation of multi-model data stores used by an application with polyglot persistence. In this research, multi-- model datasets were synthesized in order to simulate that application. We evaluate the performance of benchmarks based on a set of basic database operations on single model and multimodel data store systems. Experimental results show that in some scenarios multi-model data stores have similar or better performance than simple model data stores.
- Michael Stonebraker. 2012. What Does 'Big Data' Mean? (September 2012). Retrieved May 18, 2016 from http://cacm.acm.org/blogs/blog-cacm/155468-what-does-big-data-mean/fulltextGoogle Scholar
- Paolo Atzeni, Christian S. Jensen, Giorgio Orsi, Sudha Ram, Letizia Tanca, and Riccardo Torlone. 2013. The relational model is dead, SQL is dead and I don't feel so good myself. SIGMOD Record 42, 2 (June 2013): 64--68 Google ScholarDigital Library
- Michael Stonebraker. 2010 SQL databases v. NoSQL databases. Commun. ACM 53, 4 (2010), 10--11. Google ScholarDigital Library
- List of NoSQL Databases. Retrieved March 9, 2016 from http://nosql-database.org/Google Scholar
- Martin Fowler and Pramod Sadalage. 2013. NoSQL Distilled (1st. ed.). Addison-Wesley Professional, Boston, MA.Google Scholar
- Ingo Friepoertner. Polyglot Persistence and Multi Model Databases., Open Source Data Center Conference, Berlin, Germany (Apr 21-23 2015).Google Scholar
- Mohanty Soumendra, Jagadeesh Madhu, and Harsha Srivatsa. 2013. Big Data Imperatives (1st. ed.). APress.Google Scholar
- Veronika Abramova and Jorge Bernardino. 2013. NoSQL Databases: MongoDB vs Cassandra. Sixth International C* Conference on Computer Science & Software Engineering (C3S2E), Porto, Portugal (July 10-12, 2013). Google ScholarDigital Library
- Francesca Bugiotti and Luca Cabibbo. 2013. A Comparison of Data Models and APIs of NoSQL Datastores. P21st Italian Symposium on Advanced Database Systems, Reggio Calabria, Italy (July 2013), 63--74.Google Scholar
- Salim Jouili and Valentin Vansteenberghe. 2013. An empirical comparison of graph databases. International Conference on Social Computing 2013. Alexandria, VA (Sep 8-14 2013), 708--715. Google ScholarDigital Library
- Vojtech Kolomicenko. 2013. Analysis and Experimental Comparison of Graph Databases. M.Sc. Thesis. Charles University, Prague.Google Scholar
- Robin Henricsson. 2011. Document Oriented NoSQL Databases". B.Sc. Thesis. Blekinge Institute of Technology, Karlskrona, Sweden.Google Scholar
- Rohan Narde. 2013. A Comparison of NoSQL Systems. M.Sc. Thesis. Rochester Institute of Technology, New York, USA.Google Scholar
- Giuseppe DeCandia, Deniz Hastorun, Madan Jampani, Guna Kakulapati, Avinash Lakshman, Alex Pilchin, Swaminathan Sivasubramanian, Peter Vosshall, and Werner Vogels. 2007. Dynamo: Amazon's Highly Available Key-value Store. ACM SIGOPS Op. Syst. Rev. 41, 6 (2007), 205--220. Google ScholarDigital Library
- Fay Chang, Jeffrey Dean, Sanjay Guernawat, Wilson Hsieh, Deborah Wallach, Mike Burrows, Fikes Chandra, Andrew Tushar, and Robert Gruber. 2006. Bigtable: A Distributed Storage System for Structured Data. ACM Trans. Comp. Syst. 26, 2 (2008): 1-26 Google ScholarDigital Library
- Rico Suter. 2012. MongoDB: An Introduction and Performance Analysis. Conference about Computer Science, HSR Hochschule für Technik Rapperswil, Sweden, 2012.Google Scholar
- Justin J. Miller. 2013. Graph Database Applications and Concepts with Neo4j. AIS Electronic Library, SAIS 2013, Proceedings paper 24.Google Scholar
- ArangoDB Documentation. Retrieved May 18, 2016 from https://www.arangodb.com/documentationGoogle Scholar
- OrientDB Developers. 2012. OrientDB, Hybrid Document-Store and Graph NoSQL Database (2012). Retrieved March 9, 2016 from http://orientdb.com/orientdb-vs-mongodb/Google Scholar
- A.-L. Barabási and R. Albert. 1999. Emergence of Scaling in Random Networks. Science 286 (1999), 509--512.Google ScholarCross Ref
- GraphStream, a Dynamic Graph Library. Retrieved March 9, 2016 from http://graphstream-project.org/Google Scholar
- Apache Tinkerpop graph framework. Retrieved March 9, 2016 from http://tinkerpop.apache.org/Google Scholar
- Crontab. Retrieved March 9, 2016 from https://kb.iu.edu/d/afizGoogle Scholar
- Network Time Protocol. Retrieved March 9, 2016 from https://tools.ietf.org/html/rfc5905Google Scholar
- Virtual LANs. Retrieved March 9, 2016 from ftp://ftp.hp.com/pub/networking/software/AdvTraff-Oct2005-59908853-Chap02-VLAN.pdfGoogle Scholar
- RESTful web services. 2015. Retrieved March 9, 2016 from http://www.drdobbs.com/web-development/restful-web-services-a-tutorial/240169069Google Scholar
- RestHeart the Web API for MongoDB. Retrieved March 9, 2016 from http://restheart.org/Google Scholar
Recommendations
A Comparative Performance Evaluation of Multi-Model NoSQL Databases and Polyglot Persistence
SAC '23: Proceedings of the 38th ACM/SIGAPP Symposium on Applied ComputingMulti-model databases support different NoSQL data models at once, typically a combination of relational, key-value, document, and graph models. Their expected benefits include increased versatility, reduced installation complexity, improved database ...
Utilizing a NoSQL Data Store for Scalable Log Analysis
IDEAS '15: Proceedings of the 19th International Database Engineering & Applications SymposiumA potential problem for persisting large volume of data logs with a conventional relational database is that loading massive logs produced at high rates is not fast enough due to the strong consistency model and high cost of indexing. As a possible ...
A performance evaluation of in-memory databases
The popularity of NoSQL databases has increased due to the need of (1) processing vast amount of data faster than the relational database management systems by taking the advantage of highly scalable architecture, (2) flexible (schema-free) data ...
Comments