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The Oracle NoSQL implementation of the JSON type attempts to maintain the original type used by the developer in their favorite language, even though, from the JSON point of view, it's all numeric. 🤔
Example
Let us create multiple Dicts in Python and store them in the NoSQL database in a JSON column.
I have the following result when reading the data as JSON using the SQL CLI command. From the JSON point of view, it's all numeric.
sql-> SELECT * FROM test ORDER BY id;
{"id":"1","doc":2.675}
{"id":"2","doc":2.675}
{"id":"3","doc":{"info":{"Decimal":2.675,"Float":2.675,"Number":2.675}}}
{"id":"4","doc":12345}
{"id":"5","doc":123456789123456789}
But when reading the data using the Python SDK, Oracle NoSQL implementation of the JSON type attempts to maintain the original type used by the developer.
You can use the Oracle NoSQL JSON datatype as an extensible way for your application to interact with its data without sacrificing performance, data loss precision, and maintaining the original type in your programs.
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The Oracle NoSQL implementation of the JSON type attempts to maintain the original type used by the developer in their favorite language, even though, from the JSON point of view, it's all numeric. 🤔
Example
Let us create multiple Dicts in Python and store them in the NoSQL database in a JSON column.
I have the following result when reading the data as JSON using the SQL CLI command. From the JSON point of view, it's all numeric.
But when reading the data using the Python SDK, Oracle NoSQL implementation of the JSON type attempts to maintain the original type used by the developer.
Conclusion:
You can use the Oracle NoSQL JSON datatype as an extensible way for your application to interact with its data without sacrificing performance, data loss precision, and maintaining the original type in your programs.
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