Activeloop · Rate Limits

Activeloop Rate Limits

Deep Lake's primary interface is the open-source Python SDK operating against local or self-managed cloud storage, where throughput is bounded by your own storage and compute rather than a provider rate limit. The managed Activeloop Cloud and its alpha Managed Database REST query endpoint (https://app.activeloop.ai/api/query/v1) are gated by account tier and an ACTIVELOOP_TOKEN; Activeloop does not publish specific per-account request or query rate limits. Values are not reconciled in this artifact.

Activeloop Rate Limits is the machine-readable rate-limit profile for Activeloop on the APIs.io network, conforming to the API Commons Rate Limits specification.

It captures 4 rate-limit definitions, measuring requests, queries, and storage.

The profile also includes 2 backoff/retry policies defined and response codes documented for throttled.

Tagged areas include AI, Vector Store, Data Lake, Multimodal, and Deep Learning.

4 Limits Throttle: 429
AIVector StoreData LakeMultimodalDeep LearningRate LimitingQuotasThrottling

Limits

Open-Source SDK (self-managed storage) account
requests
bounded by your own storage/compute
No Activeloop-imposed rate limit when running against local, S3, Azure, or GCP storage.
Managed Tensor Database Queries account
queries
see provider documentation
Throughput and concurrency follow account tier; no public per-account limit published.
Managed Database REST Query Endpoint (Alpha) account
requests
see provider documentation
Alpha endpoint at app.activeloop.ai/api/query/v1; no documented request rate limit.
Managed Storage Cap account
storage
varies by tier
Free Basic tier has a storage cap; Scale / Enterprise offer unlimited storage.

Policies

Tiered Limits
Capacity and support follow account tier (Basic, Scale, Enterprise).
Backoff Strategy
Clients calling the managed REST endpoint should implement exponential backoff with jitter and honor Retry-After.

Sources