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  2. Agnostic (data) - Wikipedia

    en.wikipedia.org/wiki/Agnostic_(data)

    Devices and programs [6] can become more data-agnostic by using a generic storage format to create, read, update and delete files. Formats like XML and JSON can store information in a data agnostic manner. For example, XML is data agnostic in that it can save any type of information. However, if you use Data Transform Definitions (DTD) or XML ...

  3. Service Data Objects - Wikipedia

    en.wikipedia.org/wiki/Service_Data_Objects

    Service Data Objects denote the use of language-agnostic data structures that facilitate communication between structural tiers and various service-providing entities. They require the use of a tree structure with a root node and provide traversal mechanisms (breadth/depth-first) that allow client programs to navigate the elements. Objects can ...

  4. Database abstraction layer - Wikipedia

    en.wikipedia.org/wiki/Database_abstraction_layer

    Database abstraction layers reduce the amount of work by providing a consistent API to the developer and hide the database specifics behind this interface as much as possible. There exist many abstraction layers with different interfaces in numerous programming languages. If an application has such a layer built in, it is called database ...

  5. Comparison of data-serialization formats - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_data...

    ^ Omitted XML elements are commonly decoded by XML data binding tools as NULLs. Shown here is another possible encoding; XML schema does not define an encoding for this datatype. ^ The RFC CSV specification only deals with delimiters, newlines, and quote characters; it does not directly deal with serializing programming data structures.

  6. Schema-agnostic databases - Wikipedia

    en.wikipedia.org/wiki/Schema-agnostic_Databases

    The evolution of databases in the direction of heterogeneous data environments strongly impacts the usability, semiotics and semantic assumptions behind existing data accessibility methods such as structured queries, keyword-based search and visual query systems. With schema-less databases containing potentially millions of dynamically changing ...

  7. List of data structures - Wikipedia

    en.wikipedia.org/wiki/List_of_data_structures

    This is a list of well-known data structures. For a wider list of terms, see list of terms relating to algorithms and data structures. For a comparison of running times for a subset of this list see comparison of data structures.

  8. Opaque data type - Wikipedia

    en.wikipedia.org/wiki/Opaque_data_type

    In computer science, an opaque data type is a data type whose concrete data structure is not defined in an interface. This enforces information hiding, since its values can only be manipulated by calling subroutines that have access to the missing information. The concrete representation of the type is hidden from its users, and the visible ...

  9. Comparison of data structures - Wikipedia

    en.wikipedia.org/wiki/Comparison_of_data_structures

    Here are time complexities [5] of various heap data structures. The abbreviation am. indicates that the given complexity is amortized, otherwise it is a worst-case complexity. For the meaning of "O(f)" and "Θ(f)" see Big O notation. Names of operations assume a max-heap.