Files
supabase/apps/docs/content/guides/database/json.mdx
T
3dffdefd6e fix(docs) Resolve 196 mdx lint warnings for just, quickly, actually, PostgreSQL (#47358)
Closes DOCS-1057
Contributes to DOCS-1052

## I have read the
[CONTRIBUTING.md](https://github.com/supabase/supabase/blob/master/CONTRIBUTING.md)
file.

YES

## Problem

We have hundreds of MDX lint warnings in our docs going against style
best practices.

## Solution

Remove and replace in context the following:

- PostgreSQL. There was only one. There was concern about exceptions,
but I found none.
- Just
- Quickly
- Actually

### What changed

Edits follow the [Google developer documentation style
guide](https://developers.google.com/style): concise, direct, active
voice. The flagged words were removed when the sentence still read well,
or replaced when meaning needed to be preserved.

### Common patterns

| Flagged word | Approach | Example |
|---|---|---|
| **just** (filler) | Removed | "you just installed" → "you installed" |
| **just** (limiting) | **only** | "just one row" → "only one row" |
| **just like** | **like** / **the same as** | "function just like
regular users" → "function like regular users" |
| **not just** | **not only** | "not just errors" → "not only errors" |
| **quickly** (performance) | **efficiently** or removed | "find rows
quickly" → "find rows efficiently" |
| **quickly** (time) | **soon** / **rapidly** / removed | "expires too
quickly" → "expires too soon" |
| **actually** (filler) | Removed | "actually execute" → "execute"; "is
actually the most common" → "is the most common" |

## Tophatting

1. See the diff.
2. See that content continues to make sense in context.
3. Locally, `cd apps/docs` and run `pnpm run lint:mdx`.
4. Search for "just," "actually," "quickly", and "PostgreSQL" and see
there are 0 warnings.




<!-- This is an auto-generated comment: release notes by coderabbit.ai
-->
## Summary by CodeRabbit

* **Documentation**
* Updated wording across quickstarts, guides, and troubleshooting
articles for grammar, clarity, and consistent step-by-step phrasing.
* Clarified key concepts including Row Level Security policy evaluation
across Supabase products, deferred foreign key constraint behavior, and
when `EXPLAIN ANALYZE` executes queries (and related side effects).
* Refined several troubleshooting instructions and added guidance to cap
log payload size to reduce billed Logs Ingest volume.
<!-- end of auto-generated comment: release notes by coderabbit.ai -->

---------

Co-authored-by: github-actions[bot] <41898282+github-actions[bot]@users.noreply.github.com>
Co-authored-by: Nik Richers <nrichers@gmail.com>
Co-authored-by: Chris Chinchilla <chris.ward@supabase.io>
2026-06-29 09:40:25 -07:00

536 lines
15 KiB
Plaintext

---
id: 'json'
title: 'Managing JSON and unstructured data'
description: 'Using the JSON data type in Postgres.'
subtitle: 'Using the JSON data type in Postgres.'
tocVideo: 'nxeUiRz4G-M'
---
Postgres supports storing and querying unstructured data.
## JSON vs JSONB
Postgres supports two types of JSON columns: `json` (stored as a string) and `jsonb` (stored as a binary). The recommended type is `jsonb` for almost all cases.
- `json` stores an exact copy of the input text. Database functions must reparse the content on each execution.
- `jsonb` stores database in a decomposed binary format. While this makes it slightly slower to input due to added conversion overhead, it is significantly faster to process, since no reparsing is needed.
## When to use JSON/JSONB
Generally you should use a `jsonb` column when you have data that is unstructured or has a variable schema. For example, if you wanted to store responses for various webhooks, you might not know the format of the response when creating the table. Instead, you could store the `payload` as a `jsonb` object in a single column.
Don't go overboard with `json/jsonb` columns. They are a useful tool, but most of the benefits of a relational database come from the ability to query and join structured data, and the referential integrity that brings.
## Create JSONB columns
`json/jsonb` is another "data type" for Postgres columns. You can create a `jsonb` column in the same way you would create a `text` or `int` column:
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="database-method"
>
<TabPanel id="sql" label="SQL">
```sql
create table books (
id serial primary key,
title text,
author text,
metadata jsonb
);
```
</TabPanel>
<TabPanel id="dashboard" label="Dashboard">
1. Go to the [Table Editor](/dashboard/project/_/editor) page in the Dashboard.
2. Click **New Table** and create a table called `books`.
3. Include a primary key with the following properties and click save:
- Name: `id`
- Type: `int8`
- Default value: `Automatically generate as indentity`
- **title** column
- Name: `title`
- Type: `text`
- **author** column
- Name: `author`
- Type: `text`
- **metadata** column
- Name: `metadata`
- Type: `jsonb`
</TabPanel>
</Tabs>
## Inserting JSON data
You can insert JSON data in the same way that you insert any other data. The data must be valid JSON.
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="database-method"
>
<TabPanel id="sql" label="SQL">
```sql
insert into books
(title, author, metadata)
values
(
'The Poky Little Puppy',
'Janette Sebring Lowrey',
'{"description":"Puppy is slower than other, bigger animals.","price":5.95,"ages":[3,6]}'
),
(
'The Tale of Peter Rabbit',
'Beatrix Potter',
'{"description":"Rabbit eats some vegetables.","price":4.49,"ages":[2,5]}'
),
(
'Tootle',
'Gertrude Crampton',
'{"description":"Little toy train has big dreams.","price":3.99,"ages":[2,5]}'
),
(
'Green Eggs and Ham',
'Dr. Seuss',
'{"description":"Sam has changing food preferences and eats unusually colored food.","price":7.49,"ages":[4,8]}'
),
(
'Harry Potter and the Goblet of Fire',
'J.K. Rowling',
'{"description":"Fourth year of school starts, big drama ensues.","price":24.95,"ages":[10,99]}'
);
```
</TabPanel>
<TabPanel id="dashboard" label="Dashboard">
1. Go to the [Table Editor](/dashboard/project/_/editor) page in the Dashboard.
2. Select the `books` table in the sidebar.
3. Click **+ Insert row** and add 5 rows with the following properties:
{/* supa-mdx-lint-disable Rule003Spelling */}
| id | title | author | metadata |
| --- | ----------------------------------- | ---------------------- | --------------------------------------------------------------------------------------------------------------------- |
| 1 | The Poky Little Puppy | Janette Sebring Lowrey | `json {"ages":[3,6],"price":5.95,"description":"Puppy is slower than other, bigger animals."}` |
| 2 | The Tale of Peter Rabbit | Beatrix Potter | `json {"ages":[2,5],"price":4.49,"description":"Rabbit eats some vegetables."}` |
| 3 | Tootle | Gertrude Crampton | `json {"ages":[2,5],"price":3.99,"description":"Little toy train has big dreams."}` |
| 4 | Green Eggs and Ham | Dr. Seuss | `json {"ages":[4,8],"price":7.49,"description":"Sam has changing food preferences and eats unusually colored food."}` |
| 5 | Harry Potter and the Goblet of Fire | J.K. Rowling | `json {"ages":[10,99],"price":24.95,"description":"Fourth year of school starts, big drama ensues."}` |
{/* supa-mdx-lint-enable Rule003Spelling */}
</TabPanel>
<TabPanel id="js" label="JavaScript">
```js
const { data, error } = await supabase.from('books').insert([
{
title: 'The Poky Little Puppy',
author: 'Janette Sebring Lowrey',
metadata: {
description: 'Puppy is slower than other, bigger animals.',
price: 5.95,
ages: [3, 6],
},
},
{
title: 'The Tale of Peter Rabbit',
author: 'Beatrix Potter',
metadata: {
description: 'Rabbit eats some vegetables.',
price: 4.49,
ages: [2, 5],
},
},
{
title: 'Tootle',
author: 'Gertrude Crampton',
metadata: {
description: 'Little toy train has big dreams.',
price: 3.99,
ages: [2, 5],
},
},
{
title: 'Green Eggs and Ham',
author: 'Dr. Seuss',
metadata: {
description: 'Sam has changing food preferences and eats unusually colored food.',
price: 7.49,
ages: [4, 8],
},
},
{
title: 'Harry Potter and the Goblet of Fire',
author: 'J.K. Rowling',
metadata: {
description: 'Fourth year of school starts, big drama ensues.',
price: 24.95,
ages: [10, 99],
},
},
])
```
</TabPanel>
<$Show if="sdk:dart">
<TabPanel id="dart" label="Dart">
```dart
await supabase.from('books').insert([
{
'title': 'The Poky Little Puppy',
'author': 'Janette Sebring Lowrey',
'metadata': {
'description': 'Puppy is slower than other, bigger animals.',
'price': 5.95,
'ages': [3, 6],
},
},
{
'title': 'The Tale of Peter Rabbit',
'author': 'Beatrix Potter',
'metadata': {
'description': 'Rabbit eats some vegetables.',
'price': 4.49,
'ages': [2, 5],
},
},
{
'title': 'Tootle',
'author': 'Gertrude Crampton',
'metadata': {
'description': 'Little toy train has big dreams.',
'price': 3.99,
'ages': [2, 5],
},
},
{
'title': 'Green Eggs and Ham',
'author': 'Dr. Seuss',
'metadata': {
'description':
'Sam has changing food preferences and eats unusually colored food.',
'price': 7.49,
'ages': [4, 8],
},
},
{
'title': 'Harry Potter and the Goblet of Fire',
'author': 'J.K. Rowling',
'metadata': {
'description': 'Fourth year of school starts, big drama ensues.',
'price': 24.95,
'ages': [10, 99],
},
},
]);
```
</TabPanel>
</$Show>
<$Show if="sdk:swift">
<TabPanel id="swift" label="Swift">
Supabase Swift provides a convenience `AnyJSON` type.
```swift
struct Book {
val title: String,
val author: String,
val metadata: [String: AnyJSON]
}
try await supabase.from("books")
.insert(
[
Book(
title: "The Poky Little Puppy",
author: "Janette Sebring Lowrey",
metadata: [
"description": "Puppy is slower than other, bigger animals.",
"price": 5.95,
"ages": [3, 6]
]
),
Book(
title: "Tale of Peter Rabbit",
author: "Beatrix Potter",
metadata: [
"description": "Rabbit eats some vegetables.",
"price": 4.49,
"ages": [2, 5]
]
),
Book(
title: "Tootle",
author: "Gertrude Crampton",
metadata: [
"description": "Little toy train has big dreams.",
"price": 3.99,
"ages": [2, 5]
]
),
Book(
title: "Green Eggs and Ham",
author: "Dr. Seuss",
metadata: [
"description": "Sam has changing food preferences and eats unusually colored food.",
"price": 7.49,
"ages": [4, 8]
]
),
Book(
title: "Harry Potter and the Goblet of Fire",
author: "J.K. Rowling",
metadata: [
"description": "Fourth year of school starts, big drama ensues.",
"price": 24.95,
"ages": [10, 99]
]
)
]
)
```
</TabPanel>
</$Show>
<$Show if="sdk:kotlin">
<TabPanel id="kotlin" label="Kotlin">
```kotlin
@Serializable
data class BookMetadata(
val description: String,
val price: Double,
val ages: List<Int>
)
@Serializable
data class Book(
val title: String,
val author: String,
val metadata: BookMetadata
)
```
```kotlin
val data = supabase.from("books").insert(listOf(
Book("The Poky Little Puppy", "Janette Sebring Lowrey", BookMetadata("Puppy is slower than other, bigger animals.", 5.95, listOf(3, 6))),
Book("Tale of Peter Rabbit", "Beatrix Potter", BookMetadata("Rabbit eats some vegetables.", 4.49, listOf(2, 5))),
Book("Tootle", "Gertrude Crampton", BookMetadata("Little toy train has big dreams.", 3.99, listOf(2, 5))),
Book("Green Eggs and Ham", "Dr. Seuss", BookMetadata("Sam has changing food preferences and eats unusually colored food.", 7.49, listOf(4, 8))),
Book("Harry Potter and the Goblet of Fire", "J.K. Rowling", BookMetadata("Fourth year of school starts, big drama ensues.", 24.95, listOf(10, 99)))
))
```
</TabPanel>
</$Show>
<$Show if="sdk:python">
<TabPanel id="python" label="Python">
```python
supabase.from_('books').insert([
{
'title': 'The Poky Little Puppy',
'author': 'Janette Sebring Lowrey',
'metadata': {
'description': 'Puppy is slower than other, bigger animals.',
'price': 5.95,
'ages': [3, 6],
},
},
{
'title': 'The Tale of Peter Rabbit',
'author': 'Beatrix Potter',
'metadata': {
'description': 'Rabbit eats some vegetables.',
'price': 4.49,
'ages': [2, 5],
},
},
{
'title': 'Tootle',
'author': 'Gertrude Crampton',
'metadata': {
'description': 'Little toy train has big dreams.',
'price': 3.99,
'ages': [2, 5],
},
},
{
'title': 'Green Eggs and Ham',
'author': 'Dr. Seuss',
'metadata': {
'description':
'Sam has changing food preferences and eats unusually colored food.',
'price': 7.49,
'ages': [4, 8],
},
},
{
'title': 'Harry Potter and the Goblet of Fire',
'author': 'J.K. Rowling',
'metadata': {
'description': 'Fourth year of school starts, big drama ensues.',
'price': 24.95,
'ages': [10, 99],
},
},
]).execute()
```
</TabPanel>
</$Show>
</Tabs>
## Query JSON data
Querying JSON data is similar to querying other data, with a few other features to access nested values.
Postgres support a range of [JSON functions and operators](https://www.postgresql.org/docs/current/functions-json.html). For example, the `->` operator returns values as `jsonb` data. If you want the data returned as `text`, use the `->>` operator.
<Tabs
scrollable
size="small"
type="underlined"
defaultActiveId="sql"
queryGroup="language"
>
<TabPanel id="sql" label="SQL">
```sql
select
title,
metadata ->> 'description' as description, -- returned as text
metadata -> 'price' as price,
metadata -> 'ages' -> 0 as low_age,
metadata -> 'ages' -> 1 as high_age
from books;
```
</TabPanel>
<TabPanel id="js" label="JavaScript">
```js
const { data, error } = await supabase.from('books').select(`
title,
description: metadata->>description,
price: metadata->price,
low_age: metadata->ages->0,
high_age: metadata->ages->1
`)
```
</TabPanel>
<$Show if="sdk:swift">
<TabPanel id="swift" label="Swift">
```swift
try await supabase
.from("books")
.select(
"""
title,
description: metadata->>description,
price: metadata->price,
low_age: metadata->ages->0,
high_age: metadata->ages->1
"""
)
.execute()
```
</TabPanel>
</$Show>
<$Show if="sdk:kotlin">
<TabPanel id="kotlin" label="Kotlin">
```kotlin
val data = supabase.from("books").select(Columns.raw("""
title,
description: metadata->>description,
price: metadata->price,
low_age: metadata->ages->0,
high_age: metadata->ages->1
""".trimIndent()))
```
</TabPanel>
</$Show>
<$Show if="sdk:python">
<TabPanel id="python" label="Python">
```python
data = supabase.from_('books').select("""
title,
description: metadata->>description,
price: metadata->price,
low_age: metadata->ages->0,
high_age: metadata->ages->1
"""
).execute()
```
</TabPanel>
</$Show>
<TabPanel id="result" label="Result">
| title | description | price | low_age | high_age |
| ----------------------------------- | ------------------------------------------------------------------ | ----- | ------- | -------- |
| The Poky Little Puppy | Puppy is slower than other, bigger animals. | 5.95 | 3 | 6 |
| The Tale of Peter Rabbit | Rabbit eats some vegetables. | 4.49 | 2 | 5 |
| Tootle | Little toy train has big dreams. | 3.99 | 2 | 5 |
| Green Eggs and Ham | Sam has changing food preferences and eats unusually colored food. | 7.49 | 4 | 8 |
| Harry Potter and the Goblet of Fire | Fourth year of school starts, big drama ensues. | 24.95 | 10 | 99 |
</TabPanel>
</Tabs>
## Validating JSON data
Supabase provides the [`pg_jsonschema` extension](/docs/guides/database/extensions/pg_jsonschema) that adds the ability to validate `json` and `jsonb` data types against [JSON Schema](https://json-schema.org/) documents.
Once you have enabled the extension, you can add a "check constraint" to your table to validate the JSON data:
```sql
create table customers (
id serial primary key,
metadata json
);
alter table customers
add constraint check_metadata check (
json_matches_schema(
'{
"type": "object",
"properties": {
"tags": {
"type": "array",
"items": {
"type": "string",
"maxLength": 16
}
}
}
}',
metadata
)
);
```
## Resources
- [Postgres: JSON Functions and Operators](https://www.postgresql.org/docs/current/functions-json.html)
- [Postgres JSON types](https://www.postgresql.org/docs/current/datatype-json.html)