Search results
Results from the WOW.Com Content Network
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 ...
The terms schema matching and mapping are often used interchangeably for a database process. For this article, we differentiate the two as follows: schema matching is the process of identifying that two objects are semantically related (scope of this article) while mapping refers to the transformations between the objects. For example, in the ...
Database normalization is the process of structuring a relational database in accordance with a series of so-called normal forms in order to reduce data redundancy and improve data integrity. It was first proposed by British computer scientist Edgar F. Codd as part of his relational model .
A true fully (database, schema, and table) qualified query is exemplified as such: SELECT * FROM database. schema. table. Both a schema and a database can be used to isolate one table, "foo", from another like-named table "foo". The following is pseudo code: SELECT * FROM database1. foo vs. SELECT * FROM database2. foo (no explicit schema ...
The database schema is the structure of a database described in a formal language supported typically by a relational database management system (RDBMS). The term " schema " refers to the organization of data as a blueprint of how the database is constructed (divided into database tables in the case of relational databases ).
As a superset of JSON, Ion includes the following data types null: An empty value; bool: Boolean values; string: Unicode text literals; list: Ordered heterogeneous collection of Ion values; struct: Unordered collection of key/value pairs; The nebulous JSON 'number' type is strictly defined in Ion to be one of int: Signed integers of arbitrary size
Denormalization is a strategy used on a previously-normalized database to increase performance. In computing, denormalization is the process of trying to improve the read performance of a database, at the expense of losing some write performance, by adding redundant copies of data or by grouping data.
In some domains, a few dozen different source and target schema (proprietary data formats) may exist. An "exchange" or "interchange format" is often developed for a single domain, and then necessary routines (mappings) are written to (indirectly) transform/translate each and every source schema to each and every target schema by using the interchange format as an intermediate step.