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  2. Semi-structured data - Wikipedia

    en.wikipedia.org/wiki/Semi-structured_data

    Semi-structured data [1] is a form of structured data that does not obey the tabular structure of data models associated with relational databases or other forms of data tables, but nonetheless contains tags or other markers to separate semantic elements and enforce hierarchies of records and fields within the data.

  3. Document-oriented database - Wikipedia

    en.wikipedia.org/wiki/Document-oriented_database

    A document-oriented database is a specialized key-value store, which itself is another NoSQL database category. In a simple key-value store, the document content is opaque. A document-oriented database provides APIs or a query/update language that exposes the ability to query or update based on the internal structure in the document. This ...

  4. Object Exchange Model - Wikipedia

    en.wikipedia.org/wiki/Object_Exchange_Model

    The Object Exchange Model [1] (OEM) is a model for exchanging semi-structured data between object-oriented databases. It serves as the basic data model in numerous projects of the Stanford University Database Group, including Tsimmis, Lore, and C3. [2] Slight variations of OEM have evolved across different Stanford projects.

  5. Data model - Wikipedia

    en.wikipedia.org/wiki/Data_model

    Overview of a data-modeling context: Data model is based on Data, Data relationship, Data semantic and Data constraint. A data model provides the details of information to be stored, and is of primary use when the final product is the generation of computer software code for an application or the preparation of a functional specification to aid a computer software make-or-buy decision.

  6. Data vault modeling - Wikipedia

    en.wikipedia.org/wiki/Data_Vault_Modeling

    Datavault or data vault modeling is a database modeling method that is designed to provide long-term historical storage of data coming in from multiple operational systems. It is also a method of looking at historical data that deals with issues such as auditing, tracing of data, loading speed and resilience to change as well as emphasizing the ...

  7. Cosmos DB - Wikipedia

    en.wikipedia.org/wiki/Cosmos_DB

    It is designed to provide high availability, scalability, and low-latency access to data for modern applications. Unlike traditional relational databases, Cosmos DB is a NoSQL (meaning "Not only SQL", rather than "zero SQL") and vector database, [1] which means it can handle unstructured, semi-structured, structured, and vector data types. [2]

  8. Outline of databases - Wikipedia

    en.wikipedia.org/wiki/Outline_of_databases

    The following is provided as an overview of and topical guide to databases: Database – organized collection of data, today typically in digital form. The data are typically organized to model relevant aspects of reality (for example, the availability of rooms in hotels), in a way that supports processes requiring this information (for example, finding a hotel with vacancies).

  9. XML database - Wikipedia

    en.wikipedia.org/wiki/XML_database

    This process is important in applications where structured and semi-structured data co-exist and must be integrated perfectly. For example, extracting hierarchical data from relational databases and converting it into XML is a common approach when generating XML feeds, exchanging data between systems, or implementing XML-based configurations.