NoSQL Tutorial: Learn NoSQL Features, Types, What is, AdvantagesNoSQL is an approach to database design that can accomodate a wide variety of data models, including key-value, document, columnar and graph formats. NoSQL databases are especially useful for working with large sets of distributed data. The NoSQL term can be applied to some databases that predated the relational database management system , but it more commonly refers to the databases built in the early s for the purpose of large-scale database clustering in cloud and web applications. In these applications, requirements for performance and scalability outweighed the need for the immediate, rigid data consistency that the RDBMS provided to transactional enterprise applications. Notably, the NoSQL systems were not required to follow an established relational schema. Large-scale web organizations such as Google and Amazon used NoSQL databases to focus on narrow operational goals and employ relational databases as adjuncts where high-grade data consistency is necessary. Early NoSQL databases for web and cloud applications tended to focus on very specific characteristics of data management.
This item in chinese. Feb 28, 10 min read. Allen Wang. Nowadays, NoSQL databases co-exist with relational databases in enterprise data architecture. Most existing NoSQL databases are designed with more consideration on application performance, less on high level business models, data integration and data standardization. There is a gap between data modeling and physical data aspects of NoSQL databases. Unified data modeling supports features like document schema of NoSQL databases and reverse engineering of data from an existing database.
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NoSQL database is used for distributed data stores with humongous data storage needs. NoSQL is used for Big data and real-time web apps. For example, companies like Twitter, Facebook, Google that collect terabytes of user data every single day.
It seems that you're in Germany. We have a dedicated site for Germany. Authors: Meier , Andreas, Kaufmann , Michael. The authors thoroughly review the current state of database tools and techniques, and examine coming innovations. The book opens with a broad look at data management, including an overview of information systems and databases, and an explanation of contemporary database types:. Chapter-length treatment is afforded Data Modeling in both relational and graph databases, including enterprise-wide data architecture, and formulas for database design. The book benefits readers including students and practitioners working across the broad field of applied information technology.
A document-oriented database , or document store , is a computer program designed for storing, retrieving and managing document-oriented information, also known as semi-structured data. Document-oriented databases are one of the main categories of NoSQL databases, and the popularity of the term "document-oriented database" has grown  with the use of the term NoSQL itself. XML databases are a subclass of document-oriented databases that are optimized to work with XML documents. Graph databases are similar, but add another layer, the relationship , which allows them to link documents for rapid traversal. Document-oriented databases are inherently a subclass of the key-value store , another NoSQL database concept. The difference lies in the way the data is processed; in a key-value store, the data is considered to be inherently opaque to the database, whereas a document-oriented system relies on internal structure in the document in order to extract metadata that the database engine uses for further optimization. Although the difference is often moot due to tools in the systems, [a] conceptually the document-store is designed to offer a richer experience with modern programming techniques.
ER : Conceptual Modeling pp Cite as. We propose a database design methodology for NoSQL systems. This intermediate representation can be then implemented in target NoSQL databases, taking into account their specific features. Overall, the methodology aims at supporting scalability, performance, and consistency, as needed by next-generation web applications. Unable to display preview. Download preview PDF.