Streaming infrastructure for data delivery

When data must move continuously and react fast, streaming infrastructure carries it. This guide covers streaming infrastructure for data delivery.

When streaming fits

Streaming suits continuous, event-driven data, telemetry, transactions, signals, where consumers react as events arrive. For periodic analysis, batch is simpler and cheaper.

Brokers and protocols

Event-streaming platforms (such as Kafka) and lightweight messaging (such as MQTT) move data with different trade-offs, throughput, footprint and semantics. The choice follows the use case.

Delivery guarantees

Streaming systems offer different guarantees, at-most-once, at-least-once, exactly-once, with cost and complexity trade-offs. Ordering and de-duplication matter where correctness depends on them.

Scaling and resilience

Partitioning, back-pressure, replay and monitoring make streams production-grade. Without them, high-volume streams fail under load or lose data silently.

Sourcing considerations

Source latency caps stream freshness, and personal data in streams needs in-pipeline aggregation or anonymisation. Security applies to live infrastructure.

In a managed model

A managed partner can deliver data over streaming infrastructure with the guarantees and resilience your use case needs.

Delivery guarantees and resilience

Streaming platforms differ in the guarantees they offer, at-most-once, at-least-once, exactly-once, with cost and complexity trade-offs, and ordering and de-duplication matter where correctness depends on them. Production-grade streams also need partitioning, back-pressure handling, replay and monitoring; without these, high-volume streams fail under load or lose data silently.

Choosing by use case

Streaming suits continuous, event-driven, reactive data; for periodic analysis, batch is simpler and cheaper. Source latency caps stream freshness, and personal data in streams needs in-pipeline aggregation or anonymisation, with security applied to live infrastructure.

Sources & further reading

• Apache Kafka and CNCF streaming references.
• OASIS: MQTT specification.
• Industry references on streaming guarantees.
• Internal practice: DataSupplier streaming delivery.