Search results
Results from the WOW.Com Content Network
A SHACL validation engine takes as input a graph to be validated (called data graph) and a graph containing SHACL shapes declarations (called shapes graph) and produces a validation report, also expressed as a graph. All these graphs can be represented in any Resource Description Framework (RDF) serialization formats including JSON-LD or Turtle.
SQL:2016 or ISO/IEC 9075:2016 (under the general title "Information technology – Database languages – SQL") is the eighth revision of the ISO (1987) and ANSI (1986) standard for the SQL database query language. It was formally adopted in December 2016. [1] The standard consists of 9 parts which are described in some detail in SQL.
AI Vector Search [13] (includes new Vector data type, Vector indexes, and Vector SQL operators/functions), JSON Relational Duality, [14] JSON Schema Validation, Transactional Microservices Support, OKafka, Operational Property Graphs, Support for SQL/PGQ, Schema Privileges, Developer Role, In-database SQL Firewall, TLS 1.3 Support, Integration ...
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] JSON Schema is based on the concepts from XML Schema (XSD) but is JSON-based. As in XSD, the same ...
A DB schema based on JSONB always has fewer tables: one may nest attribute–value pairs in JSONB type fields of the Entity table. That makes the DB schema easy to comprehend and SQL queries concise. [31] The programming code to manipulate the database objects on the abstraction layer turns out much shorter. [32]
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 ...
Data validation is intended to provide certain well-defined guarantees for fitness and consistency of data in an application or automated system. Data validation rules can be defined and designed using various methodologies, and be deployed in various contexts. [1]
As the load phase interacts with a database, the constraints defined in the database schema – as well as in triggers activated upon data load – apply (for example, uniqueness, referential integrity, mandatory fields), which also contribute to the overall data quality performance of the ETL process.