If we export data via the API and hit the usage limit, will queries executed through the UI still run normally? Are these limits handled separately, or do they share the same quota?
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The knowledge sources indicate that Mixpanel enforces rate limits per API family, not as one shared quota across all querying mechanisms.
Query API (report export via API) has its own limit: max 5 concurrent queries and 60 queries per hour. [Rate limits]
Raw Data Export API (raw event export) has a different limit: max 100 concurrent queries, 60 queries per hour, and 3 queries per second. [Rate limits]
The docs do not explicitly state whether UI-run queries and API-run queries share the same underlying quota, or whether hitting an API rate limit would ever block UI queries. They only describe limits for the public APIs themselves.
So:
If you hit the Raw Data Export API limit, that only guarantees that further calls to that API will return 429s; the docs do not say that UI queries will be affected.
If you hit the Query API limit, that only guarantees that further Query API calls are limited; again, there is no explicit statement about impact on UI queries.
Because the documentation does not clearly describe how UI queries are counted relative to these API limits, I can’t confidently say whether UI queries will always continue to run normally when an API limit is hit. The knowledge sources simply don’t specify this.
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You’re right that the Raw Data Export API has a limit parameter capped at 100,000 events per request. [Export OpenAPI] If your query would return more than that, you need to break it into smaller chunks; the API itself won’t return more than 100k in one call.
From the docs and samples, there are two main non–Data Pipelines approaches:
Split by date ranges (recommended)
Instead of trying to pull all events in one call, make multiple export calls over smaller time windows so each stays under 100k events. For example, export by day or by week, depending on your volume. Mixpanel provides a sample script that does exactly this with varied-length date ranges: you define ranges and an increment (e.g., 30 days at a time for low-volume months, 1 day at a time for high-volume months). [Varied date export]
That script uses from_date / to_date only; it doesn’t rely on properties to page through results.
Filter by event and/or where (but still respect 100k limit)
You can narrow what’s returned using:
event (JSON array of event names)
where (expression to filter events) [Export OpenAPI]
Using properties in a where clause can reduce the number of events per request (e.g., only export events where a certain property has a value), but it does not bypass the 100k limit cap. You’d still need to combine this with smaller date ranges if the filtered result is >100k.
There’s no documentation in these sources about using properties as a cursor/pagination mechanism (e.g., “export by property ranges” to walk through >100k events for the same date range), so beyond filtering to reduce volume, properties don’t provide an official workaround.
If you need to move very large volumes and want to avoid managing this splitting logic yourself, the only other documented option is Data Pipelines to a warehouse or bucket. [Export methods]
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The knowledge sources do not explicitly describe how Data Pipelines are priced on Enterprise plans (whether by data volume, number of pipelines, or both), so I can’t give a precise billing formula.
What is clear from the docs:
Data Pipelines is an add-on available for Growth and Enterprise plans. [Data Pipelines overview; Choosing plan]
On event-based Growth plans, the Data Pipelines add-on is priced as a percentage on top of your event charges (20% for Data Pipelines). [1M plan FAQ]
The docs do not say that you pay per pipeline, nor do they give a separate “per GB exported” price.
Because Enterprise pricing is customized and the documentation doesn’t break down how the Data Pipelines add-on is calculated there, the safest answer is:
Data Pipelines is an add-on tied to your plan and event volume, not clearly to the number of pipelines.
Exact Enterprise pricing (including how Data Pipelines is metered) is not documented and would need to be confirmed with Mixpanel Sales or your account manager. [MTU pricing FAQ]
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The knowledge sources do not describe a Retry-After header or its exact value/behavior for the Raw Data Export API when you hit the hourly limit, so I can’t say how that specific header is handled.
What is documented:
The Raw Data Export API has a rate limit of 60 queries per hour, 3 queries per second, and 100 concurrent queries; exceeding this returns HTTP 429. [Export OpenAPI; Rate limits]
The docs recommend, in general for rate limits, to spread queries out or consolidate multiple queries into one to reduce 429s. [Rate limits]
However, there is no explicit mention in these sources of:
Whether Retry-After is returned on 429 for Raw Data Export.
How to interpret or use that header if present.
Given that gap, the safest approach (based on general Mixpanel guidance for other APIs) is to implement your own retry with exponential backoff when you receive 429s, but the exact Retry-After behavior for Raw Data Export is not documented in the provided materials.
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