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A Trevor Stoutt
A technique for storing JSON in the database engine is to use a NoSQL database, such as MongoDB, that is specifically designed to store JSON data. NoSQL databases allow for flexible and scalable storage of JSON documents and provide fast query performance for JSON data.
Another method for storing JSON in the database engine is to use a relational database, such as MySQL, and store the JSON data as text or binary data. This method is useful for applications that need to integrate with existing relational databases. However, it can be more difficult to query JSON data stored in a relational database, as it requires parsing the JSON data (n.d.).
B Nicole Snipes
C Joshua Victor
· JSON documents can be stored in a database as a text or varchar data type. This is similar to how XML documents can be stored as a text or CLOB data type. However, storing JSON as a text or varchar data type may limit the ability to search or query the data effectively, as the database engine cannot directly process the JSON document’s structure.
· Some database engines support JSON-specific data types, such as JSON or JSONB in PostgreSQL, which allow the database engine to parse the JSON document’s structure and store it more efficiently. This is similar to using XML-specific data types, such as XMLType in Oracle, which allows for more efficient storage and processing of XML documents.
· Some database engines allow JSON documents to be stored as a binary format. This approach enables faster querying and indexing of the JSON documents, and it is similar to the binary storage approach used for XML documents in some databases, such as the XML datatype in Microsoft SQL Server.
· Some database engines, such as PostgreSQL, allow for the creation of hybrid data models that combine relational data with JSON documents. This approach is useful when you need to store structured data that has some variability or when you want to take advantage of the JSON document’s flexible structure.