![]() 'Īnother situation that may come up is needing to see if a particular key exists within a JSON document. As mentioned earlier, jsonb should be the default choice for JSON storage. For the demo's sake, I've included two columns named person and personb in the table that have the same JSON data, but stored as different data types ( person is type json and personb is type jsonb). There are two person records that I've added to the table. If you'd just like to read along with the examples below, here are a couple of the JSON "documents" that we'll be working with. If you'd like to follow along with these examples, checkout this Gist that contains the SQL to create the table and insert a couple of the records I'll be demonstrating with. Now that we've looked at the data types used to store JSON, let's look at how we can retrieve the data from our database. Primitive JSON types map directly to Postgres data types.Does not preserve whitespace, key ordering, or duplicate keys (if there are duplicates, the last key/value is kept).This means that writes will be slightly slower to convert the JSON, but reads will be quicker to process the data. jsonb on the other hand will convert valid JSON to a decomposed binary format before storing. Since the JSON is stored "as is", it must be reparsed each time it is processed. When using json the data is stored exactly as received (preserving whitespace, orders, duplicate keys). The main difference between the two types is efficiency. The json type has its use cases, but it's mostly there for backward compatibility and specialized scenarios. So which one should we choose? Based on recommendations in their documentation, jsonb is the preferred data type for storing JSON. Postgres has two data types for this purpose. PostgreSQL JSON Data TypesĪs I mentioned previously Postgres has built-in support for JSON so we won't be storing the data as raw text. ![]() Finally, Postgres has built-in support for querying and processing JSON data natively. Since Postgres is also a relational database you're able to integrate relational and non-relational data seamlessly, providing greater flexibility to users/applications consuming the data. Why go with Postgres? Maybe your team or company is invested in Postgres and doesn't want the overhead of another database provider to use and manage, then Postgres is a great option. There are so many great document database options like MongoDB, CouchDB, Azure CosmosDB, Amazon DocumentDB, and many more (most public cloud services will have an offering). ![]() If you're thinking about storing JSON, your data model is probably unstructured and does not fit well into the relational model with consistent columns, relationships, etc. I think you're right in questioning the idea, but there are some situations where it can make sense. So you may be wondering why it's a good idea to store JSON data in a relational database in the first place. If you are on a different version and something mentioned doesn't work as expected, check the docs to verify that what is mentioned in this post exists in the version you're on. The content in this post is directed at the functionality of PostgreSQL 13. Note: If you'd like to see the updated syntax for JSON support in PostgreSQL 14 checkout the post here! ![]() Let's take a look at how we can store and query this data in PostgreSQL. Home Posts About Querying JSON Data in PostgreSQL Storing JSON provides flexibility, but can add complexity.
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