## 1 Introduction  
The International Data Corporation predicts that 90% of all new applications in 2022 will be developed based on microservice architectures [1]. Microservice architecture as well as software development and IT operations (DevOps) practice, improve software development agility and flexibility, and allows enterprises to bring their digital products and services to a very competitive market faster [1, 2, 3]. In order to remain competitive, companies have started to modernize their legacy monolithic systems by decomposing them into microservices [4, 5, 6, 7, 8, 9].  
Although the topic of monolithic software migration into microservice architecture has already been explored by scientists and software engineers, there is little research on the database adaptation during the migration from a monolith architecture to a microservice architecture [4, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24]. Despite this, it is recognized that data management is a major challenge in microservices [10, 25, 26, 27, 28, 29, 30]. The primary focus of most of the research is the microservice identification within monolith application and source code decomposition into microservices. All of the existing migration methods provide very little or no recommendations on how to adopt data storage to a microservice architecture during the migration from a monolith to microservice architecture. To the best of the authors' knowledge, aside from [PERSON] et al., who proposed a technique of microservice extraction from monolith enterprise systems, there have been no further migration methods that have investigated the adaption of data storage to a microservice architecture [31].  
To bridge this gap, the authors of this research aim to propose and evaluate a new migration approach that would allow to migrate the data store from a monolith to a microservice architecture. In order to propose a migration approach, the authors first had to conduct a literature review to answer to questions: What data store to use? What database pattern to use? To evaluate the proposed approach, a proof-of-concept of migration from a monolith mainframe database to a multi-model polyglot persistence was performed. The mainframe application was chosen because it best represents a typical monolith legacy application as used by 71 percent of Fortune 500 companies [32; 33; 34]. Quality attributes defined in the ISO/IEC 25012:2008 standard were used to evaluate the data quality of the microservice with a multi-model polyglot persistence and compare it with the existing monolith mainframe application.  
Our main scientific contribution and novelty of this paper are as follows:  
1. A new approach on how to conduct database migration from a monolith architecture into a microservice architecture is proposed.
2. A new approach on how to transform the monolith data model into multi-model polyglot persistence is proposed.  
This article is a continuity on the research of legacy monolith software migration to a microservice architecture. A literature review and monolith decomposition into microservices methods have been analyzed in previous articles [35; 36].  
The rest of this paper is organized as follows. Section 2 presents a literature review on the topics of data storage in microservices, SQL vs. NoSQL, and polyglot persistence. Section 3 provides a review of the related work. Section 4 describes the proposed approach and its evaluation. Section 5 reports the results of the experimental investigation. Section 6 provides an evaluation of the data quality results. Section 7 discusses the advantages and disadvantages of the proposed migration approach. Finally, Section 8 concludes this work.