Comparison of Various NoSQL Databases for Unstructured Industrial Data
The aim of this paper is creating an overview of NoSQL databases for industrial unstructured data. This comparison will explain the reader how you to select the most appropriate database for a particular type of unstructured data such as images, videos, l
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Abstract. The aim of this paper is creating an overview of NoSQL databases for industrial unstructured data. This comparison will explain the reader how you to select the most appropriate database for a particular type of unstructured data such as images, videos, logs, etc. The article consists of three parts. The first part deals with the introduction of databases. The second part describes the specific properties of chosen databases for unstructured data. And the third part presents the results and therefore the suitability of using individual databases for specific types of industrial unstructured data. Keywords: NoSQL
Industry Unstructured data Comparison Database
1 Introduction This paper is focused on various data storage tools suitable for various types of industrial unstructured data. Currently, we are facing a huge increase in the amount of data of various types in all types of industries, which are more difficult to process and therefore it is important to choose the right storage for given type of used data. There are many ways for storage and analysis, so the main aim of this paper is to compare several storage tools. We will focus specifically on the following options: CouchDB, MongoDB, Elasticsearch, RavenDB, Neo4j, Amazon Neptune, Apache Cassandra and Oracle NoSQL. Databases are divided into two large groups, SQL and NoSQL databases. SQL is suitable for relational data with a fixed structure. NoSQL databases are suitable for data with no fixed structure. The paper will focus on describing, comparing, and creating a basic overview. Therefore, it will be necessary to explain how the individual data storage tools behave, compare different distributions, their features, advantages and disadvantages, explain which types of industrial unstructured data they are most suitable for, the storage of mentioned data and subsequent parsing and analyzation. Unstructured data represent approximately more than 80% of the all data. Unstructured data are represented as text or multimedia content. Such as text documents, pdf files, video recordings, photos, audio files, presentations etc. A database is a collection of structured or unstructured information and data that are collected, stored and controlled usually electronically in a particular computer system. It is primary controlled and managed by a database management system (DBMS). © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020 R. Silhavy et al. (Eds.): CoMeSySo 2020, AISC 1294, pp. 921–930, 2020. https://doi.org/10.1007/978-3-030-63322-6_79
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A. Vaclavova and M. Kebisek
The data and the DBMS, along with the applications that are connected with them, are referred in this article as a database system, often shortened to “database”. The most common types of databases have their data typically modeled in rows and columns and usually divided into a series of tables to ease the processing and querying of its data. This fact, allows for efficient access, management, modifications, updates, control, a
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