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  2. Comparison of data-serialization formats - Wikipedia

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

    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 ...

  3. JSON - Wikipedia

    en.wikipedia.org/wiki/JSON

    While JSON provides a syntactic framework for data interchange, unambiguous data interchange also requires agreement between producer and consumer on the semantics of specific use of the JSON syntax. [25] One example of where such an agreement is necessary is the serialization of data types that are not part of the JSON standard, for example ...

  4. JSON streaming - Wikipedia

    en.wikipedia.org/wiki/JSON_streaming

    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 ...

  5. Serialization - Wikipedia

    en.wikipedia.org/wiki/Serialization

    Flow diagram. In computing, serialization (or serialisation, also referred to as pickling in Python) is the process of translating a data structure or object state into a format that can be stored (e.g. files in secondary storage devices, data buffers in primary storage devices) or transmitted (e.g. data streams over computer networks) and reconstructed later (possibly in a different computer ...

  6. Extract, transform, load - Wikipedia

    en.wikipedia.org/wiki/Extract,_transform,_load

    For example, if you need to load data into two databases, you can run the loads in parallel (instead of loading into the first – and then replicating into the second). Sometimes processing must take place sequentially. For example, dimensional (reference) data are needed before one can get and validate the rows for main "fact" tables.

  7. JSONPath - Wikipedia

    en.wikipedia.org/wiki/JSONPath

    JSONiq [11] is a query and transformation language for JSON. XPath 3.1 [12] is an expression language that allows the processing of values conforming to the XDM [13] data model. The version 3.1 of XPath supports JSON as well as XML. jq is like sed for JSON data – it can be used to slice and filter and map and transform structured data.

  8. Smile (data interchange format) - Wikipedia

    en.wikipedia.org/wiki/Smile_(data_interchange...

    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.

  9. Graph database - Wikipedia

    en.wikipedia.org/wiki/Graph_database

    Java, SQL, Python, C++, R: Massive parallel processing (MPP) database incorporating patented engines supporting native SQL, MapReduce, and graph data storage and manipulation; provides a set of analytic function libraries and data visualization [40] TerminusDB: 11.0.6: 2023-05-03 [41] Apache 2: Prolog, Rust, Python, JSON-LD