---
title: Write to Analytics Engine
description: Write custom analytics events to Workers Analytics Engine for high-cardinality, time-series data.
image: https://developers.cloudflare.com/dev-products-preview.png
---

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# Write to Analytics Engine

Write custom analytics events to Workers Analytics Engine.

[Workers Analytics Engine](https://developers.cloudflare.com/analytics/analytics-engine/) provides time-series analytics at scale. Use it to track custom metrics, build usage-based billing, or understand service health on a per-customer basis.

Unlike logs, Analytics Engine is designed for aggregated queries over high-cardinality data. Writes are non-blocking and do not impact request latency.

## Configure the binding

Add an Analytics Engine dataset binding to your Wrangler configuration file. The dataset is created automatically when you first write to it.

* [  wrangler.jsonc ](#tab-panel-11908)
* [  wrangler.toml ](#tab-panel-11909)

JSONC

```
{  "analytics_engine_datasets": [    {      "binding": "ANALYTICS",      "dataset": "my_dataset",    },  ],}
```

TOML

```
[[analytics_engine_datasets]]binding = "ANALYTICS"dataset = "my_dataset"
```

## Write data points

* [  JavaScript ](#tab-panel-11910)
* [  TypeScript ](#tab-panel-11911)

JavaScript

```
export default {  async fetch(request, env) {    const url = new URL(request.url);
    // Write a page view event    env.ANALYTICS.writeDataPoint({      blobs: [        url.pathname,        request.headers.get("cf-connecting-country") ?? "unknown",      ],      doubles: [1], // Count      indexes: [url.hostname], // Sampling key    });
    // Write a response timing event    const start = Date.now();    const response = await fetch(request);    const duration = Date.now() - start;
    env.ANALYTICS.writeDataPoint({      blobs: [url.pathname, response.status.toString()],      doubles: [duration],      indexes: [url.hostname],    });
    // Writes are non-blocking - no need to await or use waitUntil()    return response;  },};
```

TypeScript

```
interface Env {  ANALYTICS: AnalyticsEngineDataset;}
export default {  async fetch(request: Request, env: Env): Promise<Response> {    const url = new URL(request.url);
    // Write a page view event    env.ANALYTICS.writeDataPoint({      blobs: [        url.pathname,        request.headers.get("cf-connecting-country") ?? "unknown",      ],      doubles: [1], // Count      indexes: [url.hostname], // Sampling key    });
    // Write a response timing event    const start = Date.now();    const response = await fetch(request);    const duration = Date.now() - start;
    env.ANALYTICS.writeDataPoint({      blobs: [url.pathname, response.status.toString()],      doubles: [duration],      indexes: [url.hostname],    });
    // Writes are non-blocking - no need to await or use waitUntil()    return response;  },};
```

## Data point structure

Each data point consists of:

* **blobs** (strings) - Dimensions for grouping and filtering. Use for paths, regions, status codes, or customer IDs.
* **doubles** (numbers) - Numeric values to record, such as counts, durations, or sizes.
* **indexes** (strings) - A single string used as the [sampling key](https://developers.cloudflare.com/analytics/analytics-engine/sql-api/#sampling). Group related events under the same index.

## Query your data

Query your data using the [SQL API](https://developers.cloudflare.com/analytics/analytics-engine/sql-api/):

Terminal window

```
curl "https://api.cloudflare.com/client/v4/accounts/$CLOUDFLARE_ACCOUNT_ID/analytics_engine/sql" \  --header "Authorization: Bearer $CLOUDFLARE_API_TOKEN" \  --data "SELECT blob1 AS path, SUM(_sample_interval) AS views FROM my_dataset WHERE timestamp > NOW() - INTERVAL '1' HOUR GROUP BY path ORDER BY views DESC LIMIT 10"
```

## Related resources

* [Analytics Engine documentation](https://developers.cloudflare.com/analytics/analytics-engine/) \- Full reference for Workers Analytics Engine.
* [SQL API reference](https://developers.cloudflare.com/analytics/analytics-engine/sql-api/) \- Query syntax and available functions.
* [Grafana integration](https://developers.cloudflare.com/analytics/analytics-engine/grafana/) \- Visualize Analytics Engine data in Grafana.

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