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

# Rate Limits

> Request rate limits by plan and how to handle 429 responses.

## Limits by plan

| Plan    | Requests per second | Requests per minute |
| ------- | ------------------- | ------------------- |
| Free    | 2                   | 60                  |
| Starter | 10                  | 300                 |
| Pro     | 50                  | 1,500               |

<Note>
  Rate limits apply per API key. If you need higher throughput, contact us about enterprise arrangements.
</Note>

## Rate limit headers

Every response includes headers that tell you your current limit status:

| Header                  | Description                                    |
| ----------------------- | ---------------------------------------------- |
| `X-RateLimit-Limit`     | Maximum requests allowed in the current window |
| `X-RateLimit-Remaining` | Requests remaining in the current window       |
| `X-RateLimit-Reset`     | Unix timestamp when the window resets          |

## Handling 429 responses

When you exceed the rate limit, the API returns a `429 Too Many Requests` response:

```json theme={null}
{
  "error": "Too Many Requests",
  "message": "Rate limit exceeded. Please slow down.",
  "retry_after": 2
}
```

The `retry_after` field tells you how many seconds to wait before retrying.

## Recommended retry strategy

Use exponential backoff when you receive a `429`:

```javascript theme={null}
async function callWithRetry(fn, maxRetries = 3) {
  for (let attempt = 0; attempt < maxRetries; attempt++) {
    try {
      return await fn()
    } catch (err) {
      if (err.status === 429 && attempt < maxRetries - 1) {
        const wait = Math.pow(2, attempt) * 1000 // 1s, 2s, 4s
        await new Promise(resolve => setTimeout(resolve, wait))
      } else {
        throw err
      }
    }
  }
}
```

## Bulk processing tips

If you are processing large lists of contacts:

* **Batch in parallel, not all at once** — send groups of 5–10 concurrent requests rather than flooding the endpoint
* **Respect `retry_after`** — honour the value in the `429` response rather than using a fixed delay
* **Use bundle endpoints** — `contact-intel` and `fraud-signals` reduce your total request count by combining lookups