Glossary

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Glossary / Evaluation and implementation guide

Streaming Ingestion

Streaming ingestion is the continuous capture and delivery of events into a storage destination as they occur, rather than in scheduled batches.

It is the transport step: it moves events from sources like websites and applications into a warehouse or lake.

It is distinct from stream processing, which computes on events in motion; ingestion only lands the data.

A practical example

Label: example. A prospect requests a demo on your site.

With streaming ingestion, that event lands in the warehouse within seconds, so a real-time scoring job can flag the account and alert sales before the meeting request is even answered.

What to evaluate before investing

  • Ask for the vendor's typical end-to-end latency from event emission to queryable warehouse row, and what happens during traffic spikes.
  • Check whether delivery is at-least-once with deduplication, since retries can create duplicate events that distort counts.
  • Verify how the pipeline behaves during an outage: are events buffered at the source, or does real-time scoring run on gaps?

Limitations and tradeoffs

Streaming ingestion reduces delivery latency but not analysis readiness; raw streams often need transformation before scoring, and continuous pipelines cost more than batch loads.

Plan your next step with MeshLine

Connect this decision to your automation, organic marketing and customer lifecycle management. In a MeshLine demo, discuss your existing tools, the scope you need and how to measure the result.