What are Bulk Metrics

Bulk Metrics endpoints are designed to return large datasets in a single request or through pagination.
They are intended for data ingestion, backfills, analytics pipelines, and internal sync processes — not for real-time UI polling.

When to use Bulk Metrics

Use bulk endpoints when you need to:

• Ingest historical data into a database

• Run backtests or research across long time ranges

• Sync large datasets on a scheduled basis

• Retrieve multiple fields or entities in one request

If you only need a single metric series for a chart or indicator, metric endpoints are the preferred option.

Response structure

Bulk Metrics endpoints typically return a paginated response with the following structure:

• offset – starting position of the current page

• total – total number of available records

• results – array of data objects

• meta (optional) – additional response context

This structure allows efficient iteration over large datasets.

Pagination behaviour

Most bulk endpoints support pagination using:

• Skip – number of records to skip

• Take – number of records to return per request

Clients are expected to paginate until all required data is retrieved.

Credit usage considerations

Bulk requests generally consume more API credits than single-metric endpoints due to:

• Larger response sizes

• Increased processing cost

For large backfills, it is recommended to:

• Use pagination responsibly

• Avoid repeated full-history requests

• Cache results whenever possible

Important notes

• Bulk endpoints are not optimised for low-latency use cases.

• Excessive or abusive usage may trigger rate limiting.

• Schema stability is guaranteed, but available fields may vary by endpoint.