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An application of AI methods for refining the storage strategy in multi-model database systems: A survey
Miháľ, Filip ; Koupil, Pavel (advisor) ; Holubová, Irena (referee)
Multi-Model database systems combine the advantages of traditional and NoSQL database systems. However, the management of these systems is challenging, as users have to design an appropriate storage strategy for their data. One of the most influential factors in the storage strategy is the selection of indexes. Indexes can significantly improve query performance, but they require additional storage space and maintenance overhead. Index selection problem is well-studied in the context of single-model Database Management Systems (DBMSs), but there is a lack of research in the context of multi-model database systems. We address this problem by conducting a survey of current state-of-the-art index selection algorithms and evaluating their applicability to other DBMSs. The results reveal the strengths and weaknesses of existing algorithms and highlight the need for specialized algorithms for multi-model database systems. Moreover, we formulate open questions and suggest future research directions in this field. Our research provides a foundation for the development of efficient index selection algorithms for multi-model DBMSs. 1
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Unified Querying of Multi-Model Data
Crha, Daniel ; Holubová, Irena (advisor) ; Pokorný, Jaroslav (referee)
The vast majority of current multi-model querying solutions require the user to have intimate knowledge of the specific models involved. There exists a single approach for truly unified multi-model querying, but this approach is not practically usable for most users due to its complexity. In this thesis we present MMQL, a multi-model query lan- guage based on category theory, which was designed using SPARQL as a basis. Using MMQL, users can formulate multi-model, multi-database queries without needing to know about the way the data is stored. We also present our proposal for the implemen- tation of MMQL, including the required supporting algorithms. To verify the validity of our proposal, we built the proof-of-concept tool MM-quecat, an implementation of basic MMQL concepts. We then evaluated MM-quecat in a scenario involving PostgreSQL and MongoDB, querying both databases with a single MMQL query. As we present one of the first ever approaches for unified multi-model querying, we also analyze the weak- nesses and limitations of the proposed approach, opening the door for future iterations and improvements. 1
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Modelling and Management of Multi-Model Data
Koupil, Pavel ; Holubová, Irena (advisor) ; Klettke, Meike (referee) ; Krátký, Michal (referee)
Title: Modelling and Management of Multi-Model Data Author: Pavel Koupil (Čontoš) Department: Department of Software Engineering Supervisor: doc. RNDr. Irena Holubová, Ph.D., Department of Software Engi- neering Abstract: With the advent of multi-model database management systems, the boundaries of many approaches to data processing were pushed. The aspect of multi-model data introduces a new dimension of complexity and new chal- lenges not seen in single-model systems. We have to address issues arising from the combination of interconnected and often contradictory logical models, such as, e.g., order-preserving/-ignorant, aggregate-oriented/-ignorant, schema-full/- less/-mixed approaches, intra- and inter-model references, intra- and inter-model integrity constraints, or full and partial intra- and inter-model data redundancy. Hence, a number of mature and verified approaches for various data manage- ment tasks commonly used for single-model DBMSs cannot be directly applied to multi-model DBMSs. This thesis aims to propose a new family of unified approaches for both conceptual and logical multi-model modelling and data management. We first analyse the state-of-the-art of related areas. Then we propose abstract data structures to represent multi-model schema and data. These structures are then utilised...
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Evolution Management in Multi-Model Databases
Bártík, Jáchym ; Holubová, Irena (advisor) ; Nečaský, Martin (referee)
Multi-model databases allow us to combine the advantages of various data models by storing different types of data in different models. However, this technology is still relatively immature, lacks standardization, and there are not any tools that would allow us to model multi-model data or manage their evolution. This thesis (i) provides an in- troduction to MM-cat, i.e., the framework for modeling multi-model data, (ii) describes the implementation of the framework, (iii) designs a workflow and a set of schema modi- fication operations to facilitate evolution management and (iv) performs experiments to prove their reliability and scalability. 1
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Model-driven approach for data schema definitions modeling
Stenchlák, Štěpán ; Nečaský, Martin (advisor) ; Holubová, Irena (referee)
This work analyzes, formalizes, and implements a framework for multi-level concep- tual modeling of various serialization formats based on Model-Driven Architecture and previously developed tools XCase and eXolutio. It enables users to model their schema from a conceptual model in one general form from which multiple schema formats can be derived alongside documentation and transformation scripts. The thesis introduces base formalisms and findings and analyzes advanced requirements for the following work in this area, such as evolution and inheritance of schemas. The primary use case of the tool is modeling formal open standards for publishing open data for the government and public institutions of the Czech Republic. Nevertheless, the intent is to make the tool for general schema modeling. 1
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Comparative Analysis of Multi-model Databases
Guliyev, Eldar ; Holubová, Irena (advisor) ; Koupil, Pavel (referee)
BACHELOR THESIS ABSTRACT Eldar Guliyev Comparative Analysis of Multi-model Databases The thesis is devoted to performance analysis of multi-model database management systems. Data models, multi-model DBMS and query languages were studied. Based on comparison of existing database benchmarks and multi-model DBMS functionality, requirements to the benchmarking process were identified. For the performance benchmarking, a cross-platform benchmarking application with graphical user interface was designed and implemented. The benchmarking application has a plugin architecture giving the possibility to create a DLL-plugin and test a DBMS which is not supported in the initial release. ArangoDB, RavenDB and MongoDB were tested with focus on document and graph data models.
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Schema Inference for Multi-model Data
Hricko, Sebastián ; Holubová, Irena (advisor) ; Kopecký, Michal (referee)
In recent years, multi-model databases have become very popular as the individual models better suit the different domains, use cases or scenarios. NoSQL databases are an integral part of the multi-model world of big and variable datasets. While the usage of these databases is relatively simple and functional, in some cases, we lack insight into the structure of the data and the possible interconnection between the data in various databases and different models. This thesis presents a novel approach that generates a schema of the multi-model data concerning the undeclared relationships between the models. Firstly we analyse the existing single-model approaches and point out the main flaws. We then propose the universal multi-model approach and implement it as a proof of concept. 1
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XML Schema Evolution
Malý, Jakub ; Holubová, Irena (advisor) ; Klímek, Jakub (referee)
In the presented work we study the XML data evolution, reasons and consequences of XML schema evolution in particular. The thesis contains a survey of the existing approaches to this problem. The approach presented in this work extends the XSem conceptual model with the support for multiple versions of the model. Thanks to this extension, it is possible to define a set of changes between two versions of a schema. The thesis contains a description of an algorithm that compares two versions of a schema and produces a revalidation script in XSL.
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Production Line Control System
Vysoký, Přemysl ; Forst, Libor (advisor) ; Holubová, Irena (referee)
Thesis describes an implementation of a corporate system designed for ma- nagement and control of an assembly line production. The system is a PHP ap- plication with MySQL database and a web user interface. System design is based on generalized demands of a real company where the software is being used. The solution includes user and user group administration, an editor and a viewer of a manufacturing manuals of the assembly line products and an assembly line production control itself. Software allows creating an assembly line and work- place schemes, defining product parameters, creating manufacturing procedures and linking products with their manufacturing manuals. The system is designed for an easy integration of new extensions and supports a large scale of screen resolutions. 1
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Similarity of XML Data
Stárka, Jakub ; Holubová, Irena (advisor) ; Klímek, Jakub (referee)
In the present work we study the possibilities of reverse engineering of XML schemas. The work contains a survey of XML and commonly used languages for describing XML schemas, an overview of existing techniques for conceptual modeling, reverse engineering and methods for the mapping evaluation between XML schemas. A new method, based on analysis of the conceptual model XSEM and the subsequent creation of a decision tree, is introduced. The method allows effectively nd a mapping from XML schemas to models XSEM. The work also describes a new technique for selection of the path between the mapped classes. Finally, the work contains a number of experiments that show the advantages and disadvantages of the proposed solutions.
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