Abstract
Smart apps in the twenty-first century can use any data from real-world objects properties, behaviours, and events. Thus, the amount and variety of data, from structured to unstructured, are growing. The integration of data from many sources produces a wide range of variability. NoSQL database popularity has increased due to its flexible schema, easy query interface, and scalability to handle such heterogeneous data. Document oriented NoSQLs are more popular to handle such heterogeneous data with flexible schema and a semi-structured data model. A flexible schema facilitates multiple ways to represent different types of variability that exist in the data collection. However, the impact of choosing different data representations on storage, energy, and performance is unknown. On the other hand, analysing the scope of optimising storage and energy efficiency is recommended for sustainable development. This paper discusses key components of the document store schema, its alternate implementations, and empirically analyse its impact on performance, storage space, and energy requirements. The aim of this paper is to assist developers in choosing an appropriate representation of each schema component for their application in the document stores. Considering its high popularity rating, MongoDB is chosen here for empirical analysis.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
de Lima C, dos Santos Mello R (2015) A workload-driven logical design approach for NOSQL document databases. In: Proceedings of the 17th international conference on information integration and web-based applications & services, pp 1–10
Gómez P, Casallas R, Roncancio C (2016) Data schema does matter, even in NoSQL systems! In: 2016 IEEE tenth international conference on research challenges in information science (RCIS), pp 1–6
Shah M, Kothari A, Patel S (2021) Influence of schema design in NoSQL document stores. In: International conference on mobile computing and sustainable informatics. Springer, Berlin, pp 435–452
Abiteboul S (1997) Querying semi-structured data. In: Database theory ICDT’97: 6th international conference Delphi, proceedings. Springer, Berlin, pp 1–18
Atzeni P (2016) Data modelling in the NoSQL world: a contradiction? In: Proceedings of the 17th international conference on computer systems and technologies 2016. ACM, pp 1–4
Varga V, Jánosi-Rancz KT, Kálmán B (2016) Conceptual design of document NoSQL database with formal concept analysis. Acta Polytech 13(2):229–248
Chebotko A, Kashlev A, Lu S (2015) A big data modeling methodology for Apache Cassandra. In: 2015 IEEE international congress on big data, pp 238–245
Mior MJ, Salem K, Aboulnaga A, Liu R (2017) NoSE: schema design for NoSQL applications. IEEE Trans Knowl Data Eng 29(10):2275–2289
Hewasinghage M, Nadal S, Abelló A (2020) On the performance impact of using JSON, beyond impedance mismatch. In: New trends in databases and information systems: ADBIS 2020 short papers, proceedings, vol 24. Springer, Berlin, pp 73–83
Chen L, Davoudian A, Liu M (2022) A workload-driven method for designing aggregate-oriented NoSQL databases. Data Knowl Eng 142
Imam AA, Basri S, Ahmad R, Watada J, Gonzalez-Aparicio MT (2018) Automatic schema suggestion model for NoSQL document-stores databases. J Big Data 5(1):1–17
Jia T, Zhao X, Wang Z, Gong D, Ding G (2016) Model transformation and data migration from relational database to MongoDB. In: 2016 IEEE international congress on big data (BigData congress), pp 60–67
Razoqi SA (2021) Data modeling and design implementation for CouchDB database. AL-Rafidain J Comput Sci Math 15(1):39–55
Rossel G, Manna A (2020) A big data modeling methodology for NoSQL document databases. Database Syst 37
Roy-Hubara N, Sturm A, Shoval P (2021) Designing document databases: a comprehensive requirements perspective. In: Advances in conceptual modeling: workshops CoMoNoS, EmpER, proceedings, Canada, vol 40. Springer, Berlin, pp 15–25
Stanescu L, Brezovan M, Burdescu DD (2016) Automatic mapping of MySQL databases to NoSQL MongoDB. In: Federated conference on computer science and information systems. IEEE, pp 837–840
Imam AA, Basri S, Ahmad R, Aziz N, Gonzalez-Aparicio MT (2017) New cardinality notations and styles for modeling NoSQL document-store databases. In: TENCON 2017—2017 IEEE region 10 conference, pp 2765–2770
Gómez P, Roncancio C, Casallas R (2018) Towards quality analysis for document oriented bases. In: International conference on conceptual modeling. Springer, Berlin, pp 200–216
Thakkar A, Chaudhari K, Shah M (2020) A comprehensive survey on energy-efficient power management techniques. Procedia Comput Sci 167:1189–1199
Li T, Yu G, Liu X, Song J (2014) Analyzing the waiting energy consumption of NoSQL databases. In: Proceedings of 12th international conference on dependable, autonomic and secure computing, DASC 2014. IEEE, pp 277–282
Shah M, Kothari A, Patel S (2022) A comprehensive survey on energy consumption analysis for NoSQL. Scalable Comput Pract Exp 23(1):35–50
Mahajan D, Blakeney C, Zong Z (2019) Improving the energy efficiency of relational and NoSQL databases via query optimizations. Sustain Comput Inf Syst
Mahajan D, Zong Z (2017) Energy efficiency analysis of query optimizations on MongoDB and Cassandra. In: 2017 Eighth international green and sustainable computing conference (IGSC), Orlando, FL. IEEE
Bani B, Khomh F, Guéhéneuc YG (2016) A study of the energy consumption of databases and cloud patterns. In: Service-oriented computing: 14th international conference, proceedings, vol 14, Canada. Springer, Berlin, pp 606–614
Antonio B, Daniel L (2011) A call to arms: revisiting database design. ACM SIGMOD Record
Atzeni P, Bugiotti F, Cabibbo L, Torlone R (2016) Data modeling in the NoSQL world. Comput Stan Interfaces
Scherzinger S, Sidortschuck S (2020) An empirical study on the design and evolution of NoSQL database schemas. In: Conceptual modeling: 39th international conference, Vienna, Austria. Springer, Berlin, pp 441–455
Db-engines ranking (2023). https://db-engines.com/en/system/MongoDB. Last accessed on 14 Apr 2023
Badgujar J, Kale V, Shah M, Parekh R (2019) Design and simulation of single electron transistor based SRAM and its memory controller at room temperature. Int J Integr Eng 11(6):186–195
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2023 The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Shah, M., Kothari, A. (2023). Document Store Schema Design Alternatives and Their Impact. In: Swaroop, A., Polkowski, Z., Correia, S.D., Virdee, B. (eds) Proceedings of Data Analytics and Management. ICDAM 2023. Lecture Notes in Networks and Systems, vol 787. Springer, Singapore. https://doi.org/10.1007/978-981-99-6550-2_36
Download citation
DOI: https://doi.org/10.1007/978-981-99-6550-2_36
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-99-6549-6
Online ISBN: 978-981-99-6550-2
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)