An ACID-BASE Analysis of NoSQL Database Structuring Models for Efficient Data Management

Authors

DOI:

https://doi.org/10.21015/vtcs.v13i1.2167

Abstract

Due to the massive growth of data in the modern era, NoSQL databases have achieved significant popularity for their ability to scale and adapt, making them a favored option for managing extensive data in distributed systems or cloud databases. The primary goal of this research is to explore the ACID (Atomicity, Consistency, Isolation, Durability), BASE (Basically available, soft state, Eventual Consistency), and CAP (Consistency, Availability, and Partition tolerance) database structuring models to conduct a comparative analysis of ACID and BASE of twelve mostly used NoSQL databases. We also categorize each database with Brewer’s CAP theorem. This research also compares the functional and non-functional features of databases adhering to the discussed models and explores the variety of data stores from each of the four NoSQL categories (Document, Key-value, Column, and Graph). The research summarizes the suggestions, benefits, and challenges of using NoSQL databases based on their applicability to cloud-based environments.

References

S. Ferreira, J. Mendonça, and E. Andrade, "Experimental performance analysis of data consistency levels in NoSQL databases," *Software: Practice and Experience*, 2025.

I. Carvalho, F. Sá, and J. Bernardino, "Performance evaluation of NoSQL document databases: Couchbase, CouchDB, and MongoDB," *Algorithms*, vol. 16, no. 2, p. 78, 2023.

N. Bansal, S. Sachdeva, and L. K. Awasthi, "Query-based denormalization using hypergraph (QBDNH): A schema transformation model for migrating relational to NoSQL databases," *Knowledge and Information Systems*, vol. 66, no. 1, pp. 681–722, 2024.

E. Popescu and A. Radu, "A comparative study of scalability and performance in NoSQL databases for big data storage and retrieval," *Int. J. Social Analytics (IJSA)*, vol. 5, no. 12, pp. 16–27, 2020.

A. Thakare, O. W. Tembhurne, A. R. Thakare, and S. N. Reddy, "NoSQL databases: Modern data systems for big data analytics—features, categorization and comparison," *Int. J. Electr. Comput. Eng. Syst.*, vol. 14, no. 2, pp. 207–216, 2023.

I. Mapanga and P. Kadebu, "Database management systems: A NoSQL analysis," *Int. J. Modern Commun. Technol. Res. (IJMCTR)*, vol. 1, pp. 12–18, 2013.

K. Machado, R. Kank, J. Sonawane, and S. Maitra, "A comparative study of ACID and BASE in database transaction processing," *Int. J. Sci. Eng. Res.*, vol. 8, no. 5, pp. 116–119, 2017.

W. Khan et al., "SQL and NoSQL database software architecture performance analysis and assessments—a systematic literature review," *Big Data Cogn. Comput.*, vol. 7, no. 2, p. 97, 2023.

R. C. McColl et al., "A performance evaluation of open source graph databases," in *Proc. 1st Workshop Parallel Programming for Analytics Applications*, pp. 11–18, 2014.

D. Anikin, O. Borisenko, and Y. Nedumov, "Labeled property graphs: SQL or NoSQL?," in *2019 Ivannikov Memorial Workshop (IVMEM)*, pp. 7–13, IEEE, 2019.

Z. A. El Mouden et al., "Graph schema storage in SQL object-relational database and NoSQL document-oriented database: A comparative study," in *Int. Conf. Europe Middle East & North Africa Inf. Syst. Technol. Support Learning*, pp. 176–183, Springer, 2019.

Y. Zhu, E. Yan, and I. Y. Song, "The use of a graph-based system to improve bibliographic information retrieval: System design, implementation, and evaluation," *J. Assoc. Inf. Sci. Technol.*, vol. 68, no. 2, pp. 480–490, 2017.

A. Gupta et al., "NoSQL databases: Critical analysis and comparison," in *2017 Int. Conf. Comput. Commun. Technol. Smart Nation (IC3TSN)*, pp. 293–299, IEEE, 2017.

A. Makris et al., "A classification of NoSQL datastores based on key design characteristics," *Procedia Comput. Sci.*, vol. 97, pp. 94–103, 2016.

C. Vicknair et al., "A comparison of a graph database and a relational database: A data provenance perspective," in *Proc. 48th Annu. ACM Southeast Conf.*, pp. 1–6, 2010.

S. D. Dhasade, "NoSQL database," *Int. Res. J. Modernization Eng. Technol. Sci.*, vol. 4, no. 10, 2022.

C. A. Győrödi et al., "Performance analysis of NoSQL and relational databases with CouchDB and MySQL for application’s data storage," *Appl. Sci.*, vol. 10, no. 23, p. 8524, 2020.

S. Gupta and R. Rani, "A comparative study of Elasticsearch and CouchDB document oriented databases," in *2016 Int. Conf. Inventive Comput. Technol. (ICICT)*, pp. 1–4, 2016.

S. Kalid et al., "Big-data NoSQL databases: A comparison and analysis of 'BigTable', 'DynamoDB', and 'Cassandra'," in *2017 IEEE 2nd Int. Conf. Big Data Analysis (ICBDA)*, pp. 89–93, 2017.

K. Moharm and M. Eltahan, "The role of big data in improving e-learning transition," in *IOP Conf. Ser.: Mater. Sci. Eng.*, vol. 885, no. 1, p. 012003, IOP Publishing, 2020.

V. Sharma and M. Dave, "SQL and NoSQL databases," *Int. J. Adv. Res. Comput. Sci. Softw. Eng.*, vol. 2, no. 8, 2012.

S. Gupta and K. Agrawal, "NoSQL cloud based Bigdata technologies for efficient performance evaluation in the modern era," in *14th IEEE Int. Conf. Comput. Intell. Commun. Netw. (CICN)*, Al-Khobar, Saudi Arabia, pp. 350–354, 2022.

H. Vera-Olivera et al., "Data modeling and NoSQL databases—A systematic mapping review," *ACM Comput. Surv.*, vol. 54, no. 6, pp. 1–26, 2021.

P. Atzeni, F. Bugiotti, L. Cabibbo, and R. Torlone, "Data modeling in the NoSQL world," *Comput. Stand. Interfaces*, vol. 67, p. 103149, 2020.

P. Jakkula, "HBase or Cassandra? A comparative study of NoSQL database performance," *Int. J. Sci. Res. Publ.*, vol. 10, no. 3, pp. 808–820, 2020.

M. A. Abdel-Fattah, W. Mohamed, and S. Abdelgaber, "A comprehensive spark-based layer for converting relational databases to NoSQL," *Big Data Cogn. Comput.*, vol. 6, no. 3, p. 71, 2022.

E. Barbierato, M. Gribaudo, and M. Iacono, "Performance evaluation of NoSQL big-data applications using multi-formalism models," *Future Gener. Comput. Syst.*, vol. 37, pp. 345–353, 2014.

R. Kaur and J. K. Sahiwal, "A review of comparison between NoSQL databases: MongoDB and CouchDB," *Int. J. Recent Technol. Eng.*, vol. 7, pp. 892–898, 2019.

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Published

2025-06-22

How to Cite

Meghwar, H. K., & Meghji, A. F. (2025). An ACID-BASE Analysis of NoSQL Database Structuring Models for Efficient Data Management. VAWKUM Transactions on Computer Sciences, 13(1), 278–289. https://doi.org/10.21015/vtcs.v13i1.2167