> ## Documentation Index
> Fetch the complete documentation index at: https://docs.quivly.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Amazon Redshift

> Connect Redshift and map product usage metrics to your customers.

Connect Amazon Redshift to sync usage metrics into customer profiles, health scoring, and Plays. Setup has two parts: connect the warehouse, then publish a usage mapping. A successful connection alone does not start importing metrics.

## Before you start

You need a Quivly admin, your AWS Redshift endpoint and database details, and a dedicated database user with read access to the relevant schemas and tables. Quivly uses TLS connections. The endpoint must be reachable from Quivly; ask your administrator or [support@quivly.ai](mailto:support@quivly.ai) about outbound IP allowlisting if your network restricts access.

Prepare usage data with a customer identifier, date or timestamp, and event or metric values. See [warehouse data formats](/integrations/warehouses/overview.md#data-format-long-vs-wide).

## Connect Redshift

1. Open **Data → Integrations → Redshift → Configure** and add a connection.
2. Enter **Connection name**, **Host**, **Port** (5439 by default), **Database**, **User**, and **Password**.
3. Optionally enter **Schema**, or leave it blank to browse all accessible schemas.
4. Select **Test Connection**, then **Connect Redshift** after the test succeeds. Changing connection details requires testing again.

Use the connected configuration's **Add Table** control to browse accessible schemas and select usage tables. You can test the saved connection again without replacing it.

## Configure usage metrics

**1. Create a mapping**

Open **Data → Objects → Product Usage → Configuration**. Create a configuration and select the Redshift connection.

**2. Choose how to read the data**

Select a table and map its columns using **Wide** or **Long** format, or choose **Custom SQL**. Wide tables have metric columns; long tables store metric names and values in rows.

**3. Match customers and metrics**

Set the customer identifier and date columns, select the metrics to import, and choose how each metric aggregates. Review customer matching so the values reach the intended Quivly accounts.

**4. Preview and publish**

Preview real results, resolve query or mapping errors, and set the sync schedule and initial lookback. Save and publish the configuration, then check a customer's [Usage tab](/customer-views/usage-tab.md).

For **Custom SQL**, return the columns shown in the editor: `external_customer_id`, `metric_key`, numeric `value`, and `usage_date` in ISO date format. Preview the query after changing it before publishing. Queries must be read-only.

## Troubleshooting

* **Connection test fails:** Check the AWS endpoint, port, database, credentials, network access, and database user's read permissions.
* **A table is missing:** Check schema access and the optional schema filter.
* **Connected but no usage appears:** Check that the usage mapping is published, its preview returns data, and its customer identifiers match Quivly customers.
* **Need to disconnect:** Move or archive usage mappings that depend on the connection first.

For other ingestion options, see [BigQuery](/integrations/warehouses/bigquery.md), [Snowflake](/integrations/warehouses/snowflake.md), [PostHog](/integrations/product-usage/posthog.md), and the [Usage Push API](/integrations/product-usage/api-overview.md).


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