---
description: Supported data types in Cloudflare Pipelines SQL
title: SQL data types
image: https://developers.cloudflare.com/og-docs.png
---

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# SQL data types

Last updated Sep 1, 2026|Copy as Markdown| [View as Markdown](https://0285ca83.previews.developers.cloudflare.com/pipelines/sql-reference/sql-data-types/index.md)| [Agent setup](https://0285ca83.previews.developers.cloudflare.com/agent-setup/)

Cloudflare Pipelines supports a set of primitive and composite data types for SQL transformations. These types can be used in stream schemas and SQL literals with automatic type inference.

## Primitive types

| Pipelines | SQL Types | Example Literals |
| --- | --- | --- |
| `bool` | `BOOLEAN` | `TRUE`, `FALSE` |
| `int32` | `INT`, `INTEGER` | `0`, `1`, `-2` |
| `int64` | `BIGINT` | `0`, `1`, `-2` |
| `float32` | `FLOAT`, `REAL` | `0.0`, `-2.4`, `1E-3` |
| `float64` | `DOUBLE` | `0.0`, `-2.4`, `1E-35` |
| `string` | `VARCHAR`, `CHAR`, `TEXT`, `STRING` | `"hello"`, `"world"` |
| `timestamp` | `TIMESTAMP` | `'2020-01-01'`, `'2023-05-17T22:16:00.648662+00:00'` |
| `binary` | `BYTEA` | `X'A123'` (hex) |
| `json` | `JSON` | `'{"event": "purchase", "amount": 29.99}'` |

## Composite types

In addition to primitive types, Pipelines SQL supports composite types for more complex data structures.

### List types

Lists group together zero or more elements of the same type. In stream schemas, lists are declared using the `list` type with an `items` field specifying the element type. In SQL, lists correspond to arrays and are declared by suffixing another type with `[]`, for example `INT[]`.

List values can be indexed using 1-indexed subscript notation (`v[1]` is the first element of `v`).

Lists can be constructed via `[]` literals:

```sql
SELECT [1, 2, 3] as numbers
```

Pipelines provides array functions for manipulating list values, and lists may be unnested using the `UNNEST` operator.

### Struct types

Structs combine related fields into a single value. In stream schemas, structs are declared using the `struct` type with a `fields` array. In SQL, structs can be created using the `struct` function.

Example creating a struct in SQL:

```sql
SELECT struct('user123', 'purchase', 29.99) as event_data FROM events
```

This creates a struct with fields `c0`, `c1`, `c2` containing the user ID, event type, and amount.

Struct fields can be accessed via `.` notation, for example `event_data.c0` for the user ID.

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