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Managed Warehouse

GrowthBook Cloud offers a fully managed data warehouse and event tracking pipeline. Provision it in one click, send events from your app, and GrowthBook handles the rest. No infrastructure setup required.

Not sure if Managed Warehouse is right for you?

See Choose Your Data Path for a side-by-side comparison with connecting your own warehouse.

What you get​

When you provision the Managed Warehouse, GrowthBook automatically sets up your data source with everything pre-configured:

Tables​

We create 3 tables in a ClickHouse database managed by GrowthBook:

TableWhat it storesIndexed by
eventsAll custom events (page views, purchases, clicks, etc.)event_name, timestamp
experiment_viewsExperiment exposure eventsexperiment_id, timestamp
feature_usageFeature flag evaluation eventsfeature, timestamp

Fact Table​

An Events fact table is pre-built on top of the events table. This is the base you use to define metrics. It includes 16+ standard columns (timestamp, event name, device ID, and all your key attributes) and is ready to use immediately.

Starter metrics​

Three metrics are auto-created to get you started:

MetricTypeWhat it measures
Page Views per UserMeanAverage number of page views
Sessions per UserMeanAverage number of sessions
Pages per SessionRatioPage views divided by sessions

You can edit these or create your own. Read more about metrics and fact tables.

Default key attributes​

Key attributes are extracted from event data and stored as top-level columns for fast querying. We set up these defaults:

  • Identifier: device_id
  • Dimensions: geo_country, ua_browser, ua_os, ua_device_type, utm_source, utm_medium, utm_campaign

You can add more key attributes on the data source settings page. See Key Attributes for details.

Getting started​

1. Provision the Managed Warehouse​

Go to Metrics and Data → Data Sources and click Create on the Managed Warehouse option. GrowthBook provisions your ClickHouse database, tables, fact table, and starter metrics in seconds.

2. Install the SDK with tracking​

Add the GrowthBook SDK to your application with the tracking plugin enabled. Here are the two most common setups:

HTML Script Tag: add one line to your page:

<script async
  data-client-key="YOUR_CLIENT_KEY"
  data-tracking="growthbook"
  src="https://cdn.jsdelivr.net/npm/@growthbook/growthbook/dist/bundles/auto.min.js"
></script>

JavaScript / React: install the SDK and enable the tracking plugin:

import { GrowthBook } from "@growthbook/growthbook";
import {
  autoAttributesPlugin,
  growthbookTrackingPlugin
} from "@growthbook/growthbook/plugins";

const gb = new GrowthBook({
    clientKey: "YOUR_CLIENT_KEY",
    plugins: [
        autoAttributesPlugin(),
        growthbookTrackingPlugin()
    ]
});

The tracking plugin automatically sends feature usage and experiment view events. You can also log custom events:

gb.logEvent("Purchase", { amount: 49.99 });

See all supported SDKs for more options including Node.js, Python, Java, PHP, Go, and Flutter.

3. Verify events are flowing​

Open the SQL Explorer in GrowthBook and run a quick query to confirm events are arriving:

SELECT event_name, COUNT(*) AS count
FROM events
WHERE timestamp >= now() - INTERVAL 1 HOUR
GROUP BY event_name
ORDER BY count DESC

You should see your events appear within seconds of sending them.

4. Create your first metric​

Your auto-created metrics (Page Views per User, Sessions per User, Pages per Session) are ready to use immediately. To create a custom metric:

  1. Go to Metrics and Data → Fact Tables.
  2. Open the Events fact table.
  3. Click Add Metric and configure it (for example, a Proportion metric filtered to event_name = 'Purchase' to track purchase conversion rate).

Read more about metric types and configuration.

5. Run your first experiment​

With events flowing and metrics defined, you're ready to experiment:

  1. Create a feature flag in Features.
  2. Add an Experiment rule to it.
  3. Start the experiment and watch results flow in on the Results tab.

For a detailed walkthrough, see our guide to running Feature Flag Experiments.

Benefits​

  • Fully managed: No infrastructure management, scaling, or maintenance.
  • Seamless integration: One-click setup + built-in tracking in our SDKs.
  • Instant data: Events are enriched and available within seconds.
  • Raw SQL access: Use the SQL Explorer to run custom queries against your data.

How it works​

We use ClickHouse, a database optimized for real-time analytics, to store your event data. The process is:

  1. You send analytics events to our scalable ingestion API.
  2. We enrich and store them in ClickHouse within seconds.
  3. You can query the data with SQL, define metrics, and analyze experiment results with our stats engine.

Sending events​

There are 2 ways to send events to GrowthBook Cloud's Managed Warehouse:

  1. With our SDKs (limited language support).
  2. With our Ingestion API.

With SDKs​

The following SDKs have a built-in plugin to automatically send events.

For everything else, use the Ingestion API.

When the plugin is added, these SDKs will automatically send feature usage and experiment view events to GrowthBook. They also expose a helper method to log additional custom events with optional properties.

All of the attributes in the SDK are sent along with events as context. Make sure you do not include any sensitive information in your attributes (or if you do, anonymize it first).

HTML Script Tag​

Add data-tracking="growthbook" to your script tag to enable.

<script async
  data-client-key="YOUR_CLIENT_KEY"
  data-tracking="growthbook"
  src="https://cdn.jsdelivr.net/npm/@growthbook/growthbook/dist/bundles/auto.min.js"
></script>

To track additional events, use the window.gbEvents global variable. You can push events to this array, and they will be tracked.

<script>
  // Ensure the global variable exists
  window.gbEvents = window.gbEvents || [];

  // Simple (no properties)
  window.gbEvents.push("Page View");

  function handleSignUpClick() {
    // With custom properties
    window.gbEvents.push({
      eventName: "Button Click",
      properties: {
        button: "Sign Up"
      }
    });
  }
</script>
<button onclick="handleSignUpClick()">Sign Up</button>

Client-Side JavaScript / React​

Use the growthbookTrackingPlugin to enable tracking. We recommend also using the autoAttributesPlugin to include many common attributes in your events (browser, session_id, etc.).

import { GrowthBook } from "@growthbook/growthbook";
import {
  autoAttributesPlugin,
  growthbookTrackingPlugin
} from "@growthbook/growthbook/plugins";

const gb = new GrowthBook({
    clientKey: "YOUR_CLIENT_KEY",
    plugins: [
        autoAttributesPlugin(),
        growthbookTrackingPlugin()
    ]
});

Use the logEvent method to track additional custom events:

// Simple (no properties)
gb.logEvent("Page View");

// With custom properties
gb.logEvent("Button Click", {
  button: "Sign Up",
});

Node.js​

Use the growthbookTrackingPlugin to enable tracking:

import { GrowthBookClient } from "@growthbook/growthbook";
import { growthbookTrackingPlugin } from "@growthbook/growthbook/plugins";

const gb = new GrowthBookClient({
  clientKey: process.env.GROWTHBOOK_CLIENT_KEY,
  plugins: [growthbookTrackingPlugin()],
});

Use the logEvent method to track additional custom events:

gb.logEvent("Sign Up", {
  accountPlan: "pro"
}, userContext);

User-scoped instances also have a logEvent method that doesn't require the user context:

req.growthbook.logEvent("Sign Up", {
  accountPlan: "pro"
});

Ingestion API​

You can also send events directly to our ingestion API. Pass an array of event objects, each with the following properties:

  • event_name: The name of the event (e.g., "Purchase", "Button Click")
  • properties: Optional key-value pairs with properties of the event itself
  • attributes: Optional key-value pairs with attributes of the user or context at the time of the event
curl -X POST "https://us1.gb-ingest.com/track?client_key=YOUR_CLIENT_KEY" \
-H "Content-Type: application/json" \
-d '[{
  "event_name": "Purchase",
  "properties": {
    "amount": 100
  },
  "attributes": {
    "user_id": "12345"
  }
}]'

Make sure you do not include any sensitive information in your events (or if you do, anonymize it first).

Experiment view events​

In order to use GrowthBook's experiment analysis features, you must send an event every time a user views an experiment. It must match the following format:

  • event_name: Must be "Experiment Viewed"
  • properties: Must include the following key/value pairs:
    • experimentId: The ID of the experiment being viewed
    • variationId: The ID of the variation that was shown to the user

In addition, you must include attributes with the user attributes that were used to evaluate the experiment, plus any attributes you want to use as dimensions for slicing and dicing.

Feature usage events​

To take advantage of GrowthBook's feature usage analytics, you must send an event every time a feature is evaluated with a specific format.

  • event_name: Must be "Feature Evaluated"
  • properties: Must include the following key/value pairs:
    • feature: The name of the feature being evaluated
    • value: The feature's value that was returned from the evaluation
    • source: (optional) The source of the feature value (e.g., "defaultValue", "experiment", "force")
    • ruleId: (optional) The ID of the specific rule that was used to evaluate the feature (or $default if the default value was used)
    • variationId: (optional) If the value came from an experiment, the ID of the variation that was returned

Attributes​

Attributes are key-value pairs that provide context about the user or environment at the time of the event. They can be used to slice and dice your data in analysis.

It's recommended to include the same attributes you use in your GrowthBook SDK.

Some attributes are automatically enriched by the ingestion API:

  • ip: a geoip lookup is done and the following attributes are added. If an ip attribute is not provided, we use the IP address of the request.
    • geo_country
    • geo_city
    • geo_lat
    • geo_lon
  • ua: the user agent is parsed and the following attributes are added. If a user agent attribute is not provided, we use the user agent of the request.
    • ua_browser (e.g. Safari)
    • ua_os (e.g. macOS)
    • ua_device_type (e.g. mobile)
  • url: the URL is parsed and the following attributes are added:
    • url_path (e.g. /products/123)
    • url_host (e.g. www.example.com)
    • url_query (e.g. ?utm_source=google)
    • url_fragment (e.g. #section1)

It's also recommended to include attributes about which SDK is being used. This helps with debugging.

  • sdk_language (e.g. python)
  • sdk_version (e.g. 1.2.3)

Limits​

When calling the ingestion API directly, be aware of the following default limits:

  • Maximum of 100 events per request.
  • Maximum of 1 request per second.

If you need to send more than this, reach out and we can increase your limits.

Key attributes (materialized columns)​

By default, all attributes are stored as a JSON string in the attributes column of the events table. This keeps the table structure clean, but it can be more tedious and slow to query.

On the data source settings page, you can pick a set of "Key Attributes" that will be added as top-level columns in the table.

There are 2 main types of Key Attributes you should add:

  1. Identifiers: used to split traffic in experiments. Common examples are user_id, anonymous_id, and session_id.
  2. Dimensions: used to slice and dice your experiment results. Common examples are geo_country, ua_device_type, and account_plan.

You can also select Other as the type for any attributes that don't fit into the above categories. This will add them as top-level columns, but they won't be used for splitting traffic or slicing results.

note

Adding new Key Attributes does not apply retroactively to existing events. It only affects new events going forward. The GrowthBook team can help you backfill existing events with Key Attributes if needed.

SQL Explorer​

You can use the SQL Explorer to run ad-hoc queries against your events. This is useful for exploring your data, debugging issues, or creating custom reports.

note

The SQL Explorer only allows read-only SELECT queries. Write operations (INSERT, UPDATE, etc.) are prevented from being executed by the platform.

You will see 3 tables in the SQL Explorer:

  • feature_usage: contains all feature usage events
  • experiment_views: contains all experiment view events
  • events: contains all other events

SQL best practices​

Use indexes​

For best performance, take advantage of the indexed columns in each table:

  • events table:
    • timestamp: the time the event occurred
    • event_name: the name of the event (e.g., "Purchase", "Button Click")
  • feature_usage table:
    • timestamp: the time the event occurred
    • feature: the name of the feature being evaluated
  • experiment_views table:
    • timestamp: the time the event occurred
    • experimentId: the ID of the experiment being viewed

Querying attributes and properties​

If you need to access data inside attributes or properties, you can use the JSONExtract functions from ClickHouse to extract values from the JSON string. Here's an example:

SELECT
  JSONExtractString(attributes, 'geo_country') AS country,
  JSONExtractFloat(properties, 'amount') AS amount
FROM events
WHERE timestamp >= '2025-06-01 00:00:00'
  AND event_name = 'Purchase'

For attributes that are commonly used in queries, define them as Key Attributes to pull them out as top-level columns. This makes querying easier and improves performance.

Large queries​

There is a limit of 1000 rows in the SQL Explorer. Returning raw events over a large time period will quickly exceed this limit.

To work around this, use GROUP BY in your queries to aggregate results.

One common aggregation is by time intervals. You can use the toStartOf... functions in ClickHouse for this. For example, to get daily event counts:

SELECT
  toStartOfDay(timestamp) AS day,
  COUNT(*) AS count
FROM events
WHERE timestamp >= '2025-06-01 00:00:00'
GROUP BY day
ORDER BY day ASC

Whether you have thousands or millions of events, this query will always return a manageable number of rows (one per day).

There are also functions like toStartOfHour, toStartOfMonth, etc. that you can use to group by different time intervals.

FAQ​

Can I use the Managed Warehouse alongside my own warehouse?​

Yes. You can add a separate data source for your own warehouse at any time and use both simultaneously. Note that each experiment pulls data from a single data source, so you can't mix metrics from both warehouses within one experiment.

How do I add custom identifiers like user_id?​

Go to your data source settings page and add user_id as a new Key Attribute with type Identifier. Once added, include user_id in the attributes of your events and it will be extracted as a top-level column.

What happens if I exceed my event limit?​

You'll see a notification in GrowthBook when you're approaching your limit. On free plans, events stop being tracked for the remainder of the month and reset the following month. On paid plans, overage charges apply.

Can I export my data?​

You can query and export results through the SQL Explorer.

Can I use the Managed Warehouse when self-hosting?​

The Managed Warehouse is only available on GrowthBook Cloud. Self-hosted instances should connect their own data warehouse.