The Product Types Ontology for Semantic Web-based E-Commerce
PTO: The Product Types Ontology for Semantic Web-based E-Commerce
The Product Types Ontology: Good identifiers for product types based on Wikipedia
This service provides GoodRelations-compatible class definitions for any type of product or service that has an entry in the English Wikipedia.
Vocabulary: http://www.productontology.org/#
Namespace: http://www.productontology.org/
The Product Types Ontology is designed to be used in combination with GoodRelations, a standard vocabulary for the commercial aspects of offers.
See http://purl.org/goodrelations/ for more information.
2024-03-28T14:06:16.312589
The class abstracts and translations of labels are taken from Wikipedia, the free encyclopedia.
Martin Hepp
The class definition texts are taken from Wikipedia, the free encyclopedia under a Creative Commons Attribution-ShareAlike 3.0 Unported (CC BY-SA 3.0) license, see http://creativecommons.org/licenses/by-sa/3.0/. Accordingly, all ontology class definitions provided in here are available under the very same license.
E-Commerce, E-Business, GoodRelations, Ontology, Wikipedia, DBPedia
NoSQL
NoSQL (originally referring to "non-SQL" or "non-relational") is an approach to database design that focuses on providing a mechanism for storage and retrieval of data that is modeled in means other than the tabular relations used in relational databases. Instead of the typical tabular structure of a relational database, NoSQL databases house data within one data structure. Since this non-relational database design does not require a schema, it offers rapid scalability to manage large and typically unstructured data sets. NoSQL systems are also sometimes called "Not only SQL" to emphasize that they may support SQL-like query languages or sit alongside SQL databases in polyglot-persistent architectures.
Non-relational databases have existed since the late 1960s, but the name "NoSQL" was only coined in the early 2000s,triggered by the needs of Web 2.0 companies. NoSQL databases are increasingly used in big data and real-time web applications.
Motivations for this approach include simplicity of design, simpler "horizontal" scaling to clusters of machines (which is a problem for relational databases), finer control over availability, and limiting the object-relational impedance mismatch. The data structures used by NoSQL databases (e.g. key–value pair, wide column, graph, or document) are different from those used by default in relational databases, making some operations faster in NoSQL. The particular suitability of a given NoSQL database depends on the problem it must solve. Sometimes the data structures used by NoSQL databases are also viewed as "more flexible" than relational database tables.
Many NoSQL stores compromise consistency (in the sense of the CAP theorem) in favor of availability, partition tolerance, and speed. Barriers to the greater adoption of NoSQL stores include the use of low-level query languages (instead of SQL, for instance), lack of ability to perform ad hoc joins across tables, lack of standardized interfaces, and huge previous investments in existing relational databases. Most NoSQL stores lack true ACID transactions, although a few databases have made them central to their designs.
Instead, most NoSQL databases offer a concept of "eventual consistency", in which database changes are propagated to all nodes "eventually" (typically within milliseconds), so queries for data might not return updated data immediately or might result in reading data that is not accurate, a problem known as standards for distributed transaction processing. Interactive relational databases share conformational relay analysis techniques as a common feature. Limitations within the interface environment are overcome using semantic virtualization protocols, such that NoSQL services are accessible to most operating systems.
(Source: Wikipedia, the free encyclopedia, see http://en.wikipedia.org/wiki/NoSQL)
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