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Databases
Published in David Austerberry, Digital Asset Management, 2012
To retain the integrity of the data it is vital that the transaction comply with a number of conditions, usually called ACID: Atomicity: Each transaction must be either completed or aborted. It is all or nothing.Consistent: A transaction must leave the database in a consistent state. If a transaction violates the rules, then the transaction should roll back to the former consistent state.Isolated: A transaction is not available to other transactions until it is committed. If several users attempt to update the same record simultaneously, then the transactions should be performed serially and they should be isolated from each other.Durable: Once a transaction has been committed in, it should be persistent even if the system fails.
Migration from an SQL to a hybrid SQL/NoSQL data model
Published in Journal of Management Analytics, 2020
Marina V. Sokolova, Francisco J. Gómez, Larisa N. Borisoglebskaya
Traditional databases fully support requirements for ACID (Atomicity, Consistency, Isolation, and Durability) properties. In contrast, not all NoSQL databases do, or only support them partially (for example, Fuseki Apache supports write-ahead logging to provide atomicity and durability). NoSQL databases satisfy the weaker BASE (Basically Available, Soft state, Eventual consistency) model. There exist many applications of non-relative databases for DBMS, which aim to apply them to complex domains. This is the case of the paper published by Gundla and Chen (2016), where the authors present a comparison of two NoSQL databases (MongoDB and AllegroGraph). Experiments on running queries against these databases confirmed the authors' hypothesis that the search results were superior, as a traditional application database was unable to retrieve given terms.
A fresh approach for hybrid SQL/NoSQL database design based on data structuredness
Published in Enterprise Information Systems, 2018
In the past decades, the dominant database management systems have been based on relational models (SolidIT 2017). With time, relational databases have been broadened in the means of introduction of object-oriented paradigm concept, thus producing object-relational databases. Along with taking into account of characteristics of relational and object-relational databases and accepting SQL (Structured Query Language) as important feature of the aforementioned databases, and also for the sake of the simplicity of referencing them, this paper will consider the SQL databases as those based on the relational model (relational databases) and the type of databases that broadens them (object-relational databases). The main features of the relational ones are the query language support for SQL and ACID (Atomicity; Consistency; Isolation; Durability) transaction properties support, as well as a strictly designed database schema, normally rarely changed in time, which all completely complies with structured data characteristics. The lack of flexibility in the process of SQL database schema definition, along with the need for prompt storage and manipulation of a large amount of data regardless of their structuredness levels (inadequately supported by the SQL databases), has led to a novel approach: NoSQL databases. The absence of strictly defined schemas, as well as emphasizing availability on account of consistency of the data, has imposed NoSQL databases as a natural choice for unstructured data management.
Big Data technologies to process spatial and attribute data when designing and operating mine-engineering systems
Published in International Journal of Image and Data Fusion, 2019
Yuri A. Stepanov, Alexander V. Stepanov
Conventional DBMS is oriented to ACID requirements for transaction system: atomicity, consistency, isolation, and durability, whereas NoSQL involves a set of BASE features instead of ACID ones. basic availability: it is guaranteed that each request is completed (successfully or unsuccessfully).soft state: state of a system may alter as time passes, even with no entering new data, to make data consistent.eventual consistency: data may be inconsistent sometimes; however, they become consistent in a while.