{"id":73332,"date":"2020-01-15T16:43:38","date_gmt":"2020-01-15T11:13:38","guid":{"rendered":"https:\/\/www.vskills.in\/certification\/tutorial\/?p=73332"},"modified":"2024-04-12T14:27:14","modified_gmt":"2024-04-12T08:57:14","slug":"database-and-json-2","status":"publish","type":"page","link":"https:\/\/www.vskills.in\/certification\/tutorial\/database-and-json-2\/","title":{"rendered":"Database and JSON"},"content":{"rendered":"\n

Go back to Tutorial<\/a><\/p>\n\n\n

There’s been an insurgence of database management systems (DBMS) that use JSON to store data. While some of these are relational databases, most are from the NoSQL breed of DBMS. NoSQL databases typically use a different data model to the relational model that’s been so popular for many years.<\/p>\n

Database management systems that store data as JSON documents are often referred to as document store databases. They are also known as document-oriented database, aggregate database, or simply document store or document database.<\/p>\n

Each database management system has its own ways for inserting, updating, and retrieving data. Document oriented databases store their data as documents. So this means, when you insert data into a document store, you’re actually using the DBMS to create a JSON document. For example, in MongoDB, you can use insert(), insertOne(), or insertMany() to insert JSON documents into a MongoDB database.<\/p>\n

Here’s an example:<\/p>\n

db.artists.insert({<\/p>\n

artistname : “Deep Purple”,<\/p>\n

albums : [<\/p>\n

{<\/p>\n

album : “Machine Head”,<\/p>\n

year : 1972,<\/p>\n

genre : “Rock”<\/p>\n

},<\/p>\n

 <\/p>\n

{<\/p>\n

album : “Stormbringer”,<\/p>\n

year : 1974,<\/p>\n

genre : “Rock”<\/p>\n

}<\/p>\n

]\n

})<\/p>\n

As you can see, the insert() method accepts the JSON as an argument. The above statement will insert one document into the database. All the data provided is stored in one document. Once the data is in the database, you can do things like:<\/p>\n