09 August 2009

DBMS: NoSQL (Definitions)

"An umbrella term for non-relational data stores, hence the name. These stores sacrifice ACID transactions for greater scalability and availability." (Dean Wampler, "Functional Programming for Java Developers", 2011)

"A set of technologies that created a broad array of database management systems that are distinct from relational database systems. One major difference is that SQL is not used as the primary query language. These database management systems are also designed for distributed data stores." (Marcia Kaufman et al, "Big Data For Dummies", 2013)

"A class of database management systems that consist of non-relational, distributed data stores. These systems are optimized for supporting the storage and retrieval requirements of massive-scale data-intensive applications." (IBM, "Informix Servers 12.1", 2014)

"A database that doesn’t adhere to relational database structures. Used to organize and query unstructured data." (Jason Williamson, "Getting a Big Data Job For Dummies", 2015)

"Any of a class of database management systems that reject the limitations and drawbacks dictated by, or associated with, the relational model. NoSQL products tend to specialize in a single or limited number of areas, such as high-performance processing, big data (giga-record systems), diverse data types (video, pictures, mathematical models), documents, and so on. Their specialized focus often requires deemphasizing other areas such as data consistency and backup and recovery." (George Tillmann, "Usage-Driven Database Design: From Logical Data Modeling through Physical Schmea Definition", 2017)

"In general, NoSQL databases provide a mechanism for storage and retrieval of data modeled in means other than the tabular relations used in relational databases." (Prashant Natarajan et al, "Demystifying Big Data and Machine Learning for Healthcare", 2017)

"NoSQL means 'not only SQL' or 'no SQL at all'. Being a new type of non-relational databases, NoSQL databases are developed for efficient and scalable management of big data." (Zongmin Ma & Li Yan, "Towards Massive RDF Storage in NoSQL Databases: A Survey", 2019)

"A broad term for a set of data access technologies that do not use the SQL language as their primary mechanism for reading and writing data. Some NoSQL technologies act as key-value stores, only accepting single-value reads and writes; some relax the restrictions of the ACID methodology; still others do not require a pre-planned schema." (MySQL, "MySQL 8.0 Reference Manual Glossary")

"A NoSQL database is distinguished mainly by what it is not - it is not a structured relational database format that links multiple separate tables. NoSQL stands for 'not only SQL', meaning that SQL, or structured query language is not needed to extract and organize information. NoSQL databases tend to be more diverse and flatter than relational databases (in a flat database, all data is contained in the same, large table)." (Statistics.com)

"NoSQL is a database management system built for the complexities of working with Big Data. Unlike SQL, NoSQL does not store data in a relational format." (Xplenty) [source]

"No-SQL (aka not only SQL) database systems are distributed, non-relational databases designed for large-scale data storage and for massively-parallel data processing across a large number of commodity servers." (IBM) 

"NoSQL is short for 'not only SQL'. NoSQL databases include mechanisms for storage and retrieval of data based on means other than the tabular relations used in relational databases." (Idera) [source]

"sometimes referred to as ‘Not only SQL’ as it is a database that doesn’t adhere to traditional relational database structures. It is more consistent and can achieve higher availability and horizontal scaling." (Analytics Insight)

No comments:

Related Posts Plugin for WordPress, Blogger...

About Me

My photo
IT Professional with more than 24 years experience in IT in the area of full life-cycle of Web/Desktop/Database Applications Development, Software Engineering, Consultancy, Data Management, Data Quality, Data Migrations, Reporting, ERP implementations & support, Team/Project/IT Management, etc.