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Throughput

Throughput

Concepts

Throughput is the rate at which documents or operations are processed—for example, documents per minute or extraction jobs per hour. Higher throughput means more work completed per unit time. Batch processing improves throughput by handling many documents together.

Trade-offs

Latency — Faster individual responses may reduce batch throughput
Rate limits — API limits cap throughput; workflows can pace requests
Async processing — Background jobs allow high throughput without blocking

Related Concepts

Throughput matters for batch processing, document ingestion, and extraction pipelines. Latency and rate limits constrain throughput. Webhooks notify when jobs complete so you can scale processing.

Related terms

Batch Processing
Job
Latency

Frequently Asked Questions

Throughput is the rate at which documents or operations are processed (e.g., documents per minute). Batch processing and async processing improve throughput.

Rate limits, latency per operation, and concurrency. Use batch processing and webhooks to maximize throughput without blocking.

Count documents or jobs completed per minute (or hour). Use dashboard metrics, job lists, and webhook counts to track throughput.

Yes. Small text documents are faster than large PDFs or image-heavy files. OCR and parsing time dominate for scanned documents.

Throughput is usually limited at the organization level. Multiple keys may share the same quota; check whether keys have independent limits.

Sending multiple requests in parallel can increase throughput up to the rate limit. Use async and webhooks so your client is not the bottleneck.

Vector search is typically fast (milliseconds per query). Throughput is limited by the standard rate limit and backend capacity.

Yes. Submitting many documents in one or more batch requests avoids per-request overhead and uses server-side parallelism.

Workflows automate ingestion and extraction so you can sustain high throughput without manual steps. Triggers (e.g., upload) keep the pipeline fed.

See the DocLD documentation and glossary for details, and check the API reference for related endpoints and options.

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