---
title: "Materialized view"
sidebarTitle: "Materialized View"
description: "Create, open, list and drop a table whose contents are defined by a query."
icon: table
keywords: ["materialized view", "create_materialized_view", "catalog", "ddl"]
availability:
  oss: available
  enterprise: available
  summary: >-
    Both offerings support materialized views. See [Enterprise compatibility](#deployment) for connection and server requirements.
---

A materialized view is a table whose contents are defined by a query over
another table. The query is recorded in the view's schema, and a refresh
brings its stored rows up to date with the source.

The result is an ordinary table -- queryable, indexable, searchable, and present
in `table_names()`. Nothing about reading it is special.

This page covers creating and managing one. Keeping it current is
[Refresh a materialized view](/feature-engineering/materialized-views).

<Note>
In SQL, see [`REFRESH MATERIALIZED VIEW`](/sql/dml/refresh#refresh-materialized-view) and [`SHOW MATERIALIZED VIEWS`](/sql/ddl/materialized-view#show).
</Note>

## Create a materialized view {#create}

<CodeGroup>
```python Python icon="python"
view = db.create_materialized_view(
    "recent_docs",
    source="documents",
    select=["id", "title", "embedding"],
    where="created_at > TIMESTAMP '2026-01-01 00:00:00'",
)
```

```typescript TypeScript icon="square-js"
const view = await db.createMaterializedView("recent_docs", "documents", {
  select: ["id", "title", "embedding"],
  where: "created_at > TIMESTAMP '2026-01-01 00:00:00'",
});
```
</CodeGroup>

`source` names the table the view reads. With Python SDK 0.40.0, create that
table with stable row IDs before creating the view. The
[complete example](/feature-engineering/materialized-views#create-and-refresh)
shows the setup. `select`, `where` and `limit` define the query.

## Open, list and drop views {#manage}

| | Python | TypeScript | SQL |
| --- | --- | --- | --- |
| create | `create_materialized_view` | `createMaterializedView` | `CREATE MATERIALIZED VIEW` |
| open | `open_materialized_view` | `openMaterializedView` | -- |
| list | `list_materialized_views` | `listMaterializedViews` | `SHOW MATERIALIZED VIEWS` |
| refresh | `refresh` | `refresh` | `REFRESH MATERIALIZED VIEW` |
| drop | `drop_table` | `dropTable` | `DROP TABLE` |

<Note>
On a local database, `list_materialized_views` reads table schemas to find
views. On Enterprise, it asks the server for the view listing, as
`SHOW MATERIALIZED VIEWS` does.
</Note>

A view is dropped with `drop_table`, because a materialized view **is** a table.
That also means dropping one removes stored rows -- unlike dropping a
[view](/management/view), which removes only a saved query.

## Read the view and its definition {#working}

`view.table` is the underlying table, for querying, indexing, or search.
`view.definition` contains the query's select list, predicate and limit. Both are properties; on an async view, the definition is read with
`await view.definition()`.

## Enterprise compatibility {#deployment}

Enterprise supports creating and refreshing materialized views on remote
compute. Use the SDK version supported by your deployment, or the
[SQL interface](/sql/ddl/materialized-view). See
[Enterprise refreshes](/feature-engineering/materialized-views#availability)
for compatibility considerations when upgrading an existing pipeline.

## Related guides {#next}

<CardGroup cols={2}>
  <Card title="Refresh a materialized view" icon="arrows-rotate" href="/feature-engineering/materialized-views">
    How a refresh works, and what it writes.
  </Card>
  <Card title="Views" icon="eye" href="/management/view">
    The non-materialized counterpart, defined in SQL.
  </Card>
</CardGroup>