---
title: "Materialized views"
sidebarTitle: "Materialized views"
description: "Derive a table from a query over another table, and keep it current incrementally."
icon: table
keywords: ["materialized view", "create_materialized_view", "refresh", "incremental"]
---

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; a refresh computes
the rows.

The result is an ordinary table. It can be queried, indexed, and searched, and
it appears in `table_names()` — nothing about reading it is special.

## Create and refresh {#create-and-refresh}

```python
import lancedb

db = lancedb.connect(
    "./.lancedb",
    storage_options={"new_table_enable_stable_row_ids": "true"},
)
table = db.create_table("people", [{"name": "ada", "age": 36},
                                   {"name": "kid", "age": 7}])

view = db.create_materialized_view(
    "adults",
    "people",
    select=["name", ("shout", "upper(name)")],
    where="age >= 18",
)

result = view.refresh()
result.rows_written
# 1
```

`select` takes column names, `(alias, expression)` pairs, or a dict of the same.
Omitting it selects every source column, expanded against the schema as it was
at creation time. `where` filters source rows; `limit` caps the view.

## The source needs stable row ids {#stable-row-ids}

<Warning>
The source table must have been created with stable row ids:

```python
db = lancedb.connect(uri, storage_options={"new_table_enable_stable_row_ids": "true"})
```

They are what keeps the view's provenance valid when the source is compacted,
and **they cannot be enabled after a table exists**. A table created without
them cannot later become the source of a view — it has to be recreated.
</Warning>

This is the one decision here that is hard to undo, so it is worth setting the
option on any table you might later want to derive from.

## Refreshes are incremental {#incremental}

`refresh()` reconciles the source's changes into the view — rows added, changed,
or removed since the last refresh — rather than recomputing from scratch. It
falls back to a full rebuild when the changes cannot be reconciled.

Two arguments override that:

- `full=True` forces a rebuild.
- `source_version=N` refreshes against that source version instead of the
  latest, which is how you make a view reproduce a known point in time.

Concurrent refreshes of one view do not duplicate rows. If two plan the same
source rows, they conflict on commit and the loser raises rather than writing
them twice — so a retry loop around `refresh()` is safe.

## Local databases only {#availability}

<Warning>
Materialized views are supported on **local databases**. Calling
`create_materialized_view` on a remote connection raises `NotImplementedError`.

This is the reverse of [functions](/feature-engineering/functions), which run
only against Cloud and Enterprise. If you are deriving tables on a remote
database, a [computed column](/feature-engineering/computed-columns) filled by a
server job is usually the closer fit.
</Warning>

## Working with the view {#working-with-the-view}

`view.table()` returns the underlying table for querying, indexing, or search.
`view.definition()` returns the recorded query — the select list, predicate, and
limit — which is how you check what a view actually contains without inferring
it from the rows.

An existing view is reopened with `db.open_materialized_view(name)`.

## What to read next {#next}

<CardGroup cols={2}>
  <Card title="Computed columns" icon="table-columns" href="/feature-engineering/computed-columns">
    Derive a column instead of a whole table.
  </Card>
  <Card title="Versioning" icon="clock-rotate-left" href="/tables/versioning">
    Every refresh commits a table version.
  </Card>
</CardGroup>