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JSON: No Smile Format Specification: Yes No Yes Partial (JSON Schema Proposal, other JSON schemas/IDLs) Partial (via JSON APIs implemented with Smile backend, on Jackson, Python) — SOAP: W3C: XML: Yes W3C Recommendations: SOAP/1.1 SOAP/1.2: Partial (Efficient XML Interchange, Binary XML, Fast Infoset, MTOM, XSD base64 data) Yes Built-in id ...
Smile is a computer data interchange format based on JSON.It can also be considered a binary serialization of the generic JSON data model, which means tools that operate on JSON may be used with Smile as well, as long as a proper encoder/decoder exists for the tool.
JSON Schema specifies a JSON-based format to define the structure of JSON data for validation, documentation, and interaction control. It provides a contract for the JSON data required by a given application and how that data can be modified. [ 29 ]
Free and open-source software portal; Zorba is an open source query processor written in C++, [1] implementing . several W3C XQuery and XML specifications and; the JSONiq language for processing JSON data.
JSON streaming comprises communications protocols to delimit JSON objects built upon lower-level stream-oriented protocols (such as TCP), that ensures individual JSON objects are recognized, when the server and clients use the same one (e.g. implicitly coded in). This is necessary as JSON is a non-concatenative protocol (the concatenation of ...
YAML (/ ˈ j æ m əl /, rhymes with camel [4]) was first proposed by Clark Evans in 2001, [15] who designed it together with Ingy döt Net [16] and Oren Ben-Kiki. [16]Originally YAML was said to mean Yet Another Markup Language, [17] because it was released in an era that saw a proliferation of markup languages for presentation and connectivity (HTML, XML, SGML, etc.).
JSON-LD is designed around the concept of a "context" to provide additional mappings from JSON to an RDF model. The context links object properties in a JSON document to concepts in an ontology. In order to map the JSON-LD syntax to RDF, JSON-LD allows values to be coerced to a specified type or to be tagged with a language.
Speed and efficiency – UBJSON uses data representations that are (roughly) 30% smaller than their compacted JSON counterparts and are optimized for fast parsing. Streamed serialisation is supported, meaning that the transfer of UBJSON over a network connection can start sending data before the final size of the data is known.