{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T22:20:07Z","timestamp":1775082007972,"version":"3.50.1"},"reference-count":17,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T00:00:00Z","timestamp":1768867200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Future Internet"],"abstract":"<jats:p>The exponential growth of data generated by modern digital applications, including systems inspired by Industrial Internet of Things (IIoT) requirements, has accelerated the adoption of NoSQL databases due to their scalability, flexibility, and performance advantages over traditional relational systems. Among document-oriented solutions, MongoDB and RavenDB stand out due to their architectural features and their ability to manage dynamic, large-scale datasets. This paper presents a comparative analysis of MongoDB and RavenDB, focusing on the performance of fundamental CRUD (Create, Read, Update, Delete) operations. To ensure a controlled performance evaluation, a mobile and web application for managing product orders was implemented as a case study inspired by IIoT data characteristics, such as high data volume and frequent transactional operations, with experiments conducted on datasets ranging from 1000 to 1,000,000 records. Beyond the core CRUD evaluation, the study also investigates advanced operational scenarios, including joint processing strategies (lookup versus document inclusion), bulk data ingestion techniques, aggregation performance, and full-text search capabilities. These complementary tests provide deeper insight into the systems\u2019 architectural strengths and their behavior under more complex and data-intensive workloads. The experimental results highlight MongoDB\u2019s consistent performance advantage in terms of response time, particularly with large data volumes, while RavenDB demonstrates competitive behavior and offers additional benefits such as built-in ACID compliance, automatic indexing, and optimized mechanisms for relational retrieval and bulk ingestion. The analysis does not propose a new benchmarking methodology but provides practical insights for selecting an appropriate document-oriented database for data intensive mobile and web application contexts, including IIoT-inspired data characteristics, based on a controlled single-node experimental setting, while acknowledging the limitations of a single-host experimental environment.<\/jats:p>","DOI":"10.3390\/fi18010057","type":"journal-article","created":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T13:02:07Z","timestamp":1768914127000},"page":"57","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Performance Evaluation of MongoDB and RavenDB in IIoT-Inspired Data-Intensive Mobile and Web Applications"],"prefix":"10.3390","volume":"18","author":[{"given":"M\u0103d\u0103lina","family":"Ciumac","sequence":"first","affiliation":[{"name":"Faculty of Electrical Engineering and Information Technology, University of Oradea, 410087 Oradea, Romania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7815-4355","authenticated-orcid":false,"given":"Cornelia Aurora","family":"Gy\u0151r\u00f6di","sequence":"additional","affiliation":[{"name":"Department of Computers and Information Technology, University of Oradea, 410087 Oradea, Romania"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7027-5750","authenticated-orcid":false,"given":"Robert \u0218tefan","family":"Gy\u0151r\u00f6di","sequence":"additional","affiliation":[{"name":"Department of Computers and Information Technology, University of Oradea, 410087 Oradea, Romania"}]},{"given":"Felicia Mirabela","family":"Costea","sequence":"additional","affiliation":[{"name":"Department of Computers and Information Technology, University of Oradea, 410087 Oradea, Romania"}]}],"member":"1968","published-online":{"date-parts":[[2026,1,20]]},"reference":[{"key":"ref_1","first-page":"214","article-title":"Big Data Analytics: A Literature Review Paper","volume":"Volume 8","author":"Elgendy","year":"2014","journal-title":"Advances in Data Analysis and Classification, Proceedings of the ICDM 2014, St. Petersburg, Russia, 16\u201320 July 2014"},{"key":"ref_2","unstructured":"Han, J., Haihong, E., Le, G., and Du, J. (2011, January 26\u201328). Survey on NoSQL Database. Proceedings of the 2011 6th International Conference on Pervasive Computing and Applications (ICPCA), Gqeberha, South Africa."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1145\/1978915.1978919","article-title":"Scalable SQL and NoSQL Data Stores","volume":"39","author":"Cattell","year":"2011","journal-title":"ACM SIGMOD Rec."},{"key":"ref_4","doi-asserted-by":"crossref","unstructured":"Carvalho, I., S\u00e1, F., and Bernardino, J. (2023). Performance Evaluation of NoSQL Document Databases: Couchbase, CouchDB, and MongoDB. Algorithms, 16.","DOI":"10.3390\/a16020078"},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Tudorica, B.G., and Bucur, C. (2011, January 23\u201325). A Comparison between Several NoSQL Databases with Comments and Notes. Proceedings of the 2011 RoEduNet International Conference 10th Edition: Networking in Education and Research, Iasi, Romania.","DOI":"10.1109\/RoEduNet.2011.5993686"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"1686","DOI":"10.21275\/MS241126103744","article-title":"Emerging Trends and Challenges in Modern Database Technologies: A Comprehensive Analysis","volume":"13","author":"Miryala","year":"2024","journal-title":"Int. J. Sci. Res. (IJSR)"},{"key":"ref_7","doi-asserted-by":"crossref","unstructured":"Martins, P., S\u00e1, F., Caldeira, F., and Abbasi, M. (2022, January 20\u201322). NoSQL: A Real Use Case. Proceedings of the International Conference on Disruptive Technologies, Tech Ethics and Artificial Intelligence, Salamanca, Spain.","DOI":"10.1007\/978-3-030-87687-6_23"},{"key":"ref_8","unstructured":"(2025, March 18). MongoDB Documentation. Available online: https:\/\/www.mongodb.com\/docs."},{"key":"ref_9","unstructured":"RavenDB (2025, March 18). RavenDB vs. MongoDB. Available online: https:\/\/ravendb.net\/ravendb-vs-mongodb#fullComparison."},{"key":"ref_10","unstructured":"(2025, March 18). RavenDB Documentation. Available online: https:\/\/ravendb.net\/docs."},{"key":"ref_11","doi-asserted-by":"crossref","unstructured":"Mili\u010di\u0107, D. (2022). Introducing RavenDB, Apress.","DOI":"10.1007\/978-1-4842-8919-8"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1186\/2192-113X-2-22","article-title":"Data Management in Cloud Environments: NoSQL and NewSQL Data Stores","volume":"2","author":"Grolinger","year":"2013","journal-title":"J. Cloud Comput. Adv. Syst. Appl."},{"key":"ref_13","unstructured":"Gillenson, M.L. (2023). Fundamentals of Database Management Systems, John Wiley & Sons."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"183","DOI":"10.32996\/jcsts.2024.6.2.21","article-title":"MongoDB and Data Consistency: Bridging the Gap Between Performance and Reliability","volume":"6","author":"Dhanagari","year":"2024","journal-title":"J. Comput. Sci. Technol. Stud."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"24298","DOI":"10.48084\/etasr.10620","article-title":"Evaluation of SQL and NoSQL Databases on Parallel Processing","volume":"15","author":"Qaddara","year":"2025","journal-title":"Eng. Technol. Appl. Sci. Res."},{"key":"ref_16","unstructured":"Sharma, M. (2021). MongoDB Complete Guide: Develop Strong Understanding of Administering MongoDB, CRUD Operations, MongoDB Commands, MongoDB Compass, MongoDB Server, MongoDB Replication and MongoDB Sharding, BPB Publications."},{"key":"ref_17","doi-asserted-by":"crossref","unstructured":"Mili\u010di\u0107, D. (2022). Getting Started with RavenDB. Introducing RavenDB: The Database for Modern Data Persistence, Apress.","DOI":"10.1007\/978-1-4842-8919-8"}],"container-title":["Future Internet"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/1999-5903\/18\/1\/57\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,1,20]],"date-time":"2026-01-20T13:12:16Z","timestamp":1768914736000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/1999-5903\/18\/1\/57"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,1,20]]},"references-count":17,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2026,1]]}},"alternative-id":["fi18010057"],"URL":"https:\/\/doi.org\/10.3390\/fi18010057","relation":{},"ISSN":["1999-5903"],"issn-type":[{"value":"1999-5903","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,1,20]]}}}