pg_jsonschema: JSON Schema support for Postgres

19 Aug 2022

6 minute read

Released on the Supabase platform today, pg_jsonschema is a Postgres extension which adds JSON Schema validation support for json and jsonb data types.

The use-case for JSON validation

Despite Supabase being an SQL shop, even our most zealous relational data model advocates (begrudgingly) recognize some advantages to the document data model. Mainly, if some complex data will always be consumed together, a document data type can be a good fit.

For Example:

If our application receives data via a webhook:


_21
{
_21
"status_code": 200,
_21
"checksum": "89b623f6332d2b9b42b4e17eaf1bcc60"
_21
"headers": {
_21
"Content-Type": "application/json",
_21
"Last-Modified": "Tue, 09 Aug 2022 09:14:10 GMT"
_21
},
_21
"payload": {
_21
{
_21
"success": true,
_21
"content": {
_21
"account_id": "d928b484-16bd-4f10-a827-3eb959b4cc14",
_21
"event": "SUBSCRIBED",
_21
"subscriptions": [
_21
{"subscription_id": 481, "exp": 1660050940},
_21
{"subscription_id": 121, "exp": 1660041852},
_21
]
_21
}
_21
}
_21
}
_21
}

A reasonable swing at normalizing that data into tables might look like this:

That's a lot of architecting! Moreover, the query to recover the original input requires 5 joins!

A solution that aligns better with our intent would be to persist whatever we receive from the external service so long as it meets a minimum set of requirements. With Postgres' json data type we can achieve half of that goal.

Treating the webhook contents as a json document simplifies our data model. It is also robust to changing payloads and more efficient to query, update, and delete.

Now what about this part?

so long as it meets a minimum set of requirements

Challenges

The flexibility of document types also comes with some downsides.

The schema of the json payload from the previous example is a little intense for a blog post, so let's instead say we intend for a table's json column to hold objects with a string attribute named foo and no additional attributes.

Without constraints, the setup would be:


_10
create table some_table (
_10
id serial primary key,
_10
metadata json not null
_10
);
_10
_10
insert into some_table (metadata)
_10
values (<SQL Input>);

But the resulting schema is much more permissive than our intent. When inserting a mix of correct and incorrect values:

Only 2 of our 8 test cases were handled appropriately by our data model.

A core strength of SQL databases is their ability to constrain data's types, nullability, referential integrity, uniqueness, and even arbitrary developer-defined rules. Those constraints are a lot to sacrifice to gain the convenience of document types.

Fortunately, the challenge of validating json documents isn't specific to SQL databases. NoSQL/Document databases, like MongoDB, optionally enforce data constraints so there's plenty of prior art for us to draw from.

JSON Schema

JSON Schema is a specification for validating the shape and contents of json documents. It can describe constraints for documents similar to those applied by relational databases.

Translating our constraints from the previous example into a JSON Schema we get:


_12
// objects with a string attribute
_12
// named foo and no additional attributes
_12
{
_12
"type": "object",
_12
"properties": {
_12
"foo": {
_12
"type": "string"
_12
}
_12
},
_12
"required": ["foo"],
_12
"additionalProperties": false
_12
}

Which is a formal and human-readable description of our intent. A tutorial on the JSON Schema language is out-of-scope for this article but you can find a full introduction in their guide.

So now we have:

✅ flexible document data type → json

✅ a language to describe constraints on json documents → JSON Schema

❌ a way to enforce JSON Schema constraints on json documents in Postgres

pg_jsonschema

pg_jsonschema is a Postgres extension that can validate json and jsonb data types against a JSON Schema. The extension offers two functions:


_10
-- Validates a json *instance* against a JSON Schema *schema*
_10
json_matches_schema(schema json, instance json) returns bool
_10
_10
-- Validates a jsonb *instance* against a JSON Schema *schema*
_10
jsonb_matches_schema(schema json, instance jsonb) returns bool

We can use those functions in combination with a check constraint to more completely describe our data model.


_24
create table some_table(
_24
id serial primary key,
_24
metadata json not null,
_24
_24
check (
_24
json_matches_schema(
_24
schema :='{
_24
"type": "object",
_24
"properties": {
_24
"foo": {
_24
"type": "string"
_24
}
_24
},
_24
"required": ["foo"],
_24
"additionalProperties": false
_24
}',
_24
instance := metadata
_24
)
_24
)
_24
);
_24
_24
insert into some_table(metadata)
_24
values
_24
(<SQL input>);

With that check constraint in place, we re-run the same test cases:

Now all 8 tests are handled correctly. In cases where records failed to insert, Postgres throws an error referencing the failing constraint.

ERROR: new row for relation "some_table" violates check constraint "some_table_metadata_check"

DETAIL: Failing row contains (1, null).

SQL state: 23514

With these tools you can wield the flexibility of json/jsonb data types without sacrificing the guarantees of a well specified data model!

To get started with pg_jsonschema, fire up a new supabase project and enable the extension with


_10
create extension pg_jsonschema;

or follow the Docker Compose instructions in the repo's README.

Share this article

Build in a weekend, scale to millions