05. Filtering, pagination and large datasets

Performance starts with respect for the amount of data. An integration that charges everything at night can make the entire operation noticeable in the morning.

The interface as a product

Pagination divides a collection into controlled pages. For a safe run it needs stable sorting, progress checkpointing, detection of changes during the run and an ending that doesn't just guess "empty answer".

This makes the connection robust

1. Choose the narrowest technical filter, such as change time, status or external key.
2. Use /api/{Controller}/Page or the documented search.
3. Stably sort via unique fields and save page/checkpoint.
4. Limit page size and parallel requests by measurement.
5. Handle added or changed records during the run with defined snapshot/delta procedure.
6. Measure duration, data volume, rate and errors.

Prove production readiness

• No data record is missing or appears twice.
• Run can be continued after interruption.
• Productive load remains within agreed limits.
• Delta window overlaps deliberately, without double effect.

Mistakes that only become expensive during operation

• Offset pagination without stable sorting skips migrating records.
• Unlimited parallelism creates timeout cascades.
• Full deduction replaces a clean change model.

This is what you take with you

Even millions of records become a predictable, continuable work stream.

Further information / source

Related topics

1. For integration specialists – connect APIs and external systems › 04. Endpoints, data contracts and answers
2. For integration specialists – connecting APIs and external systems › 09. Error diagnosis, logging and restart

Frequently asked questions