INVESTIGATION OF APPLICABILITY OF MULTIMODEL DATA WAREHOUSES IN GAMING INDUSTRY
Abstract
This paper examines the feasibility and effectiveness of using multi-model databases for storing and processing data in the gaming industry. Modern gaming projects are characterized by highly complex and heterogeneous data: from strictly structured information about players, items, and quests to semi-structured and tightly coupled data, such as recipe systems, dialog trees, clan relationships, and in-game encyclopedias. Existing approaches based on relational or single-model NoSQL storage systems often fail to provide the necessary flexibility, performance, and development ease for such complex scenarios. The aim of this study is to design and comparatively analyze the performance of a multi-model solution for typical gaming mechanics. The authors developed a multi-model storage structure based on the ArangoDB DBMS that integrates document, graph, and key-value data models. The solution architecture encompasses key RPG game components: player and inventory management, quest systems, dialogue, crafting recipes, loot tables, clan relationships, and full-text search of the in-game encyclopedia using ArangoSearch. The experimental section includes a detailed performance comparison of the developed multi-model storage system with the PostgreSQL relational DBMS and the MongoDB document DBMS on realistic datasets and queries. The results demonstrate a significant advantage of the multi-model approach when performing operations that require traversing complex relationships: for example, searching for hostile players through a clan relationship graph in ArangoDB is, on average, 11 times faster than a similar JOIN query in PostgreSQL. However, for scenarios with frequent modifications to linearly organized data (e.g., updating quest status), the multi-model storage system exhibits slightly lower performance compared to the relational model, which, however, is acceptable within the context of the overall game project architecture. The study confirms that multi-model DBMSs, particularly ArangoDB, represent a promising solution for the gaming industry, enabling efficient combination of different data models within a single platform, simplifying development, and achieving high performance on complex data, which is critical for modern multiplayer games.
References
1. List'ev D.S., Savina A.G., Malyavkina L.I. Tendentsii razvitiya igrovoy industrii [Trends in the develop-ment of the gaming industry], Tsifrovye instrumenty obespecheniya ustoychivogo razvitiya ekonomiki i obrazovaniya: novye podkhody i aktual'nye problem [Digital tools for ensuring sustainable development of economy and education: new approaches and current problems]. 2022. pp. 69-75.
2. Kishkevich D.V., Nesterenkov S.N., Markov A.N. Primenenie tekhnologii Big Data v igrovoy industrii = Application of Big Data technology in the game industry [Application of Big Data technology in the game industry], BIG DATA and Advanced Analytics = BIG DATA i analiz vysokogo urovnya: materialy VIII Mezhdunar. nauch.-prakt. konf., Minsk, 11–12 maya 2022 g. Belorus. gos. un-t informatiki i radi-oelektroniki [BIG DATA and Advanced Analytics = BIG DATA i analiz vysokogo urovnya: materials of the VIII International Scientific and Practical Conference, Minsk, May 11–12, 2022. Belarusian State University of Informatics and Radioelectronics]; editorial board: V.A. Bogush [i dr.]. Minsk, 2022, pp. 120-124.
3. Khine P.P., Wang Z. A review of polyglot persistence in the big data world, Information, 2019,
Vol. 10, No. 4, pp. 141.
4. Holubová I., Vavrek M., Scherzinger S. Evolution management in multi-model databases, Data & Knowledge Engineering, 2021, Vol. 136, Art. 101932.
5. Mihai (Rizescu) G. Multi-Model Database Systems: The State of Affairs, Annals of Dunarea de Jos University of Galati. Fascicle I. Economics and Applied Informatics, 2020, Vol. XXVI, pp. 211-215.
6. Lu J., Holubova I. Multi-model Databases: A New Journey to Handle the Variety of Data, ACM Com-puting Surveys, 2019, Vol. 52, No. 3, pp. 1-38.
7. Laputsenko A.V., Klochkova M.V. Osobennosti razlichnykh sistem upravleniya bazami dannykh [Fea-tures of various database management systems], Potentsial rossiyskoy ekonomiki i innovatsionnye puti ego realizatsii [Potential of the Russian economy and innovative ways of its implementation], 2022, pp. 337-342.
8. Jowan S.A., Faraj Swese R., Yousf Aldabrzi A., Saad Shertil M. Traditional RDBMS to NoSQL Data-base: New Era of databases for Big Data, Journal of Humanities and Applied Science, 2016, Vol. 29.
9. Alekseev A.M., Borozna V.S., Suruzhiy N.A. Sistemy upravleniya bazami dannykh. Klassifikatsiya sistem upravleniya bazami dannykh [Database management systems. Classification of database management systems], 2023.
10. Karpyuk A.D., Vlasenkova D.G. Kakie vidy SUBD i ikh realizatsii sushchestvuet i chto podkhodit luchshim obrazom dlya razrabotki avtomatizirovannykh informatsionnykh sistem? [What types of DBMS and their implementations exist and what is best suited for the development of automated infor-mation systems?], Prioritetnye napravleniya innovatsionnoy deyatel'nosti v promyshlennosti: sb. nauch. st. po itogam Chetvertoy mezhdunar. nauch. konf., Kazan', 29–30 aprelya 2020 goda [Priority direc-tions of innovative activity in industry: collection of scientific articles on the results of the Fourth Interna-tional Scientific Conference, Kazan, April 29–30, 2020]. In 2 parts. Part 2, 2020, pp. 62-64. EDN UPKNFL.
11. Stack Overflow Developer Survey 2025, Stack Overflow. Available at: https://survey.stackoverflow.co/2025 (accessed 01 August 2025).
12. Rai P.K., Singh P. International Journal of Computer Science and Mobile Computing Studies and Anal-ysis of Popular Database Models, International Journal of Computer Science and Mobile Computing, 2015, Vol. 4, No. 5, pp. 834-838.
13. Sokolov K.K. Sravnenie relyatsionnykh i nerelyatsionnykh modeley SUBD [Comparison of relational and non-relational DBMS models], Nauchnoe obespechenie tekhnicheskogo i tekhnologicheskogo pro-gressa [Scientific support of technical and technological progress], 2019, pp. 39-41.
14. Guo Q., Zhang C., Zhang S., Lu J. Multi-model query languages: taming the variety of big data, Dis-tributed and Parallel Databases, 2023, pp. 1-41.
15. Kupriyanchik E.M. Sravnitel'nyy analiz podkhodov k razrabotke prilozheniy NoSQL i SQL SUBD [Comparative analysis of approaches to application development for NoSQL and SQL DBMS],
XI Kongress molodykh uchenykh [XI Congress of Young Scientists], 2022, pp. 72-75.
16. Pokorný J. Graph databases: their power and limitations, Computer Information Systems and Industrial Management: Proc. of the 14th IFIP TC 8 International Conference, CISIM 2015, Warsaw, Poland, September 24-26, 2015. Springer International Publishing, 2015, pp. 58-69.
17. Sharipova N.N. Ob ispol'zovanii NOSQL-khranilishch dannykh [On the use of NoSQL data storages], Vostochno-Evropeyskiy nauchnyy zhurnal [East-European Scientific Journal], 2016, Vol. 9, No. 3,
pp. 73-76. EDN XRXLFF.
18. Galiguzova E.V., Illarionova Yu.E. Sravnenie relyatsionnykh i nerelyatsionnykh SUBD [Comparison of relational and non-relational DBMS], Simvol nauki [Symbol of Science], 2023, No. 1-2, pp. 14-17.
19. Postmortem of service outage at 3.4M CCU, Fortnite: Official Website. Available at: https://www.fortnite.com/news/postmortem-of-service-outage-at-3-4m-ccu (accessed 01 August 2025).
20. Bazy dannykh v onlayn-igrakh. Ot Allodov Onlayn do Skyforge [Databases in online games. From Allods Online to Skyforge], Blog kompanii VK [VK Company Blog]. Available at: https://habr.com/ru/companies/vk/articles/182088/ (accessed 01 August 2025).
21. Making Our Backside Bigger [Making Our Backside Bigger], Eve Online: Official Website [Eve Online: Official Website]. Available at: https://www.eveonline.com/news/view/making-our-backside-bigger (ac-cessed 01 August 2025).
22. Kotenko V.N., Eliseev V.O. Innovatsionnyy metod khraneniya dannykh v igrakh v zhanre Role-Playing Game [Innovative method of data storage in Role-Playing Games], Donetskie chteniya 2021: obra-zovanie, nauka, innovatsii, kul'tura i vyzovy sovremennosti [Donetsk readings 2021: education, science, innovation, culture and challenges of our time], 2021, pp. 243-246.
23. Za chashkoy kofe s razrabotchikami: klassicheskaya versiya World of Warcraft [Over a cup of coffee with the developers: the classic version of World of Warcraft], Ofitsial'nyy sayt kompanii Activision Bliz-zard [Official website of Activision Blizzard company]. Available at: https://news.blizzard.com/ ru-ru/world-of-warcraft/21881587/za-chashkoj-kofe-s-razrabotchikami-klassicheskaya-versiya-world-of-warcraft (accessed 01 August 2025).
24. Abdullah Alqwbani B., Zuping Z., Aqlan F., Alqwbani A., Zuping Z., Aqlan F. Big Data Management for MMO Games and Integrated Website Implementation, Global Journals Inc. (USA), 2014, Vol. 14, No. 6, Version 1.0.
25. MMORPG Data Storage (Part 1), Plant Based Games. Available at: https://plantbasedgames.io/ blog/posts/01-mmorpg-data-storage-part-one/ (accessed 01 August 2025).
26. Unity: The Gaming Industry in 2025, GameDev Reports, 2025. Available at: https://gamedevreports.substack.com/p/unity-the-gaming-industry-in-2025 (accessed 01 August 2025).
27. Newzoo Global Games Market Report 2024, Newzoo. Available at: https://newzoo.com/resources/ trend-reports/newzoo-global-games-market-report-2024-free-version (accessed 24 August 2025).
28. DB-Engines Ranking, DB-Engines. Available at: https://db-engines.com/en/ranking (accessed 01 August 2025).
29. Obzor mul'timodel'nykh baz dannykh [Overview of multi-model databases], Big Data School, 2023. Available at: https://bigdataschool.ru/blog/multimodel-databases-overview/ (accessed 24 August 2025).
30. NoSQL Performance Benchmark 2018 – MongoDB, PostgreSQL, OrientDB, Neo4j and ArangoDB // ArangoDB. Available at: https://arangodb.com/2018/02/nosql-performance-benchmark-2018-mongodb-postgresql-orientdb-neo4j-arangodb/ (accessed 01 August 2025).
31. Ye F., Sheng X., Nedjah N., Sun J., Zhang P. A Benchmark for Performance Evaluation of a Multi-Model Database vs. Polyglot Persistence, Journal of Database Management, 2023, Vol. 34, No. 1, pp. 1-20.
32. TimeConqueror/gamedev-multimodal-dbms, GitHub. Available at: https://github.com/TimeConqueror/ gamedev-multimodal-dbms (accessed 01 August 2025).
