Data can be stored in JSONB columns via JSON or any string types which will be implicitly casted to JSONB. Usage of JSONB data type is very similar to JSON data type. User can define columns of type JSONB in regular tables just like JSON data type columns. They are exactly same from client perspective. From server perspective JSONB data type is simply the binary format of JSON type. The new JSONB data type will be used to store JSON unstructured data in a NPS database in binary form. For the complete list please refer to the Learn more section below. In addition, we offer a number of JSON operators and functions to facilitate data manipulation. Use jsonb_pretty to make JSON query result output more readable.Here are some sample queries against JSON data type to get you started. When we insert JSON data in text string, NPS will parse and validate the data against JSON format which makes JSON data retrieval fast and easy. JSON data type helps to reduce unused space in this case. We don’t have to waste space to store NULL values in non-applicable columns any more, such as SCREEN_SIZE for headphone in sale_catalog table with traditional data types. We only insert data applicable to a specific type of product.We are able to store specifications for various products with different attributes within a single JSON type column.We can easily tell the benefits of JSON data type column. VALUES (1, 'Samsung - UR55', 'monitor', 349.99, '') Īs shown below, the 1 st result set is from the sale_catalog table without JSON column, and the 2 nd result set is from sale_catalog_using_json table with JSON column. INSERT INTO sale_catalog_using_json(id, name, type, price, specs) Let’s create the sales catalog now with a JSON data type column specs instead: - Using one single JSON column to store all product specsĬREATE TABLE sale_catalog_using_json(id INT, We can use JSON data type column to make existing table extensible without any DDL change even if we have new product specs requirements coming in. That’s when our new JSON data type comes in handy. Now the new sales catalog looks like this:Īs you can see, in order to accommodate new product attributes with traditional data types, we have to either add new columns to the existing table or add new table for new product. Now we need to add more columns to the existing catalog table because headphones come with some different attributes from monitors such as IS_WIRELESS, BATTERY_LIFE and COLOR. Our sales catalog first looks like this:Īs the store sales grows, we have started to sell headphones. It’s sufficient to use a relational table with traditional data types such as VARCHAR for the catalog. When the store first opened, we just had monitors to sell. Let’s say we have a sales catalog from a computer electronics stores. Let’s look at an example to demonstrate our new JSON data type in NPS. In addition JSON is useful to bridge the gap between relational data types and non-structured data. JSON is a very commonly used data format, with such a wide range of applications, such as the input and output format for REST APIs and IoT device. Why do we support JSON data type natively in NPS? In the future we plan to support another type, JSONPATH, to facilitate data manipulation within the JSON document even further. JSONB data type will be introduced later in this blog. We now provide compatibility functions and storage of JSON data type in the textual form as well as its binary form known as JSONB. The new JSON feature will not only allow you to work directly with JSON data type, but also bridge the gap between relational data types and non-structured data. Without this feature you would have to use various character data types and store JSON objects as plain text. Authors: Rafael Jaffarove( Hugh Nguyen( Jia Li( can now store and retrieve JSON types natively.
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