Self-adapting data migration in the context of schema evolution in NoSQL databases

Hillenbrand, Andrea; Störl, Uta; Nabiyev, Shamil; Klettke, Meike

doi:10.1007/s10619-021-07334-1

Cited by 9 publications

(2 citation statements)

References 13 publications

(14 reference statements)

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“…NoSQL databases use different data models, including graph, key-value, document, in-memory search [27]. On the other hand, NoSQL databases are designed for various data access patterns involving low latency applications [28,29]. For this reason, NoSQL database systems are not preferred in cases where low latency is important.…”

Section: Related Workmentioning

confidence: 99%

A Novel Approach to Improve the Performance of the Database Storing Big Data with Time Information

Taşyürek

2022

Balkan Journal of Electrical and Computer Engineering

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Big data is defined as data sets that are too large and/or complex to be processed by classical data processing methods. Big data analysis is essential because it enables more competent business movements, more efficient operations, and higher profits by using the data of institutions and organizations. However, large datasets are difficult to analyze because they are produced quickly, require large storage areas in computer systems, and the diversity of their data. In this study, a new approach using the denormalization method is proposed to accelerate the response time of the database in database systems where large volumes of data containing historical information are stored. Denormalization is defined as the process of adding rows or columns that are not needed to increase the reading performance of the database to the database system that has been normalized. In the proposed approach in this study, a large-volume dataset consisting of real spatial data belonging to Kayseri Metropolitan Municipality, containing temporal information and having approximately 96,000,000 row records, was used. In the proposed approach, the response time of the query is accelerated by recording the time information as numbers to increase the query performance of large volumes of data recorded in date format due to the temporal query process. The performance of the proposed method is compared with the performance of the normalization method using actual data on Microsoft SQL Server and Oracle database systems. The method proposed in the experimental evaluations shows that it works approximately eight times faster. In addition, the experimental results showed that the proposed method improves query performance more than the normalization-based method as the data size increases.

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Section: Related Workmentioning

confidence: 99%

A Novel Approach to Improve the Performance of the Database Storing Big Data with Time Information

Taşyürek

2022

Balkan Journal of Electrical and Computer Engineering

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“…Without sufficient data quality, data development is incomprehensible. present a method of self-changing data migration, which thus changes development strategies and their limits concerning the movement circumstance and organization level plans, hence adding to the self-organization of informational collection systems and supporting a deft development [9] [10]. explore information movement basics.…”

Section: Introductionmentioning

confidence: 99%

Data Migration from Visual Basic Interfaces to Excel Tables Prevent Conflict Using Proposed Models

Hashim

2022

International Journal of Computational and Applied Mathematics &Amp; Computer Science

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In relational and complex spreadsheets, relational and non-relational database models, high-speed data migration with scalable structure using visual Basic Excel programming language implementations with proposed migration model. One of the primary purposes behind making a point of interaction through the Visual Basic Application (VBA) is that most PC clients with logical preparation will currently know about Succeed and its significant capabilities (like arranging furthermore, plotting datasets). Even though Excel itself is in many cases utilized as an information storehouse by clients. The time factor, reliability, and credibility of migrating this data from one table to another through programming interfaces were measured using the link codes between the tables. In this paper, the migration and migration of homogeneous and heterogeneous data are investigated by using two types of different migration models of data to measure and match these data and the extent of their integration after migration. Specifies the target data for migration from the input tables in the Excel program to the target tables in larger databases. Furthermore, the two models (A, B) middleware provide an architecture that can be extended to support Relational database management systems (RDBMS) and other graphing databases. Experiments were performed using excel tables, both of which are related as source information bases, and as the data set for the source and target datasets, the migration time between these tables for the two models was calculated While retaining the same characteristics.

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Managing Schema Migration in NoSQL Databases: Advisor Heuristics vs. Self-adaptive Schema Migration Strategies

Hillenbrand

Störl

2023

Communications in Computer and Information Science

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Self-adapting data migration in the context of schema evolution in NoSQL databases

Cited by 9 publications

References 13 publications

A Novel Approach to Improve the Performance of the Database Storing Big Data with Time Information

A Novel Approach to Improve the Performance of the Database Storing Big Data with Time Information

Data Migration from Visual Basic Interfaces to Excel Tables Prevent Conflict Using Proposed Models

Managing Schema Migration in NoSQL Databases: Advisor Heuristics vs. Self-adaptive Schema Migration Strategies

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