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Middleware & integration

Apache Kafka & event streaming

A durable, high-speed log of events that many systems can write to and read from in real time.

  • Event streaming platform
  • Typical project: 6–14 weeks
  • Open source (Apache); managed by Confluent, AWS, Azure and others

Overview

Kafka stores streams of events, such as “order placed” or “sensor reading”, in order and for as long as you like. Producers write events; any number of consumers read them at their own pace, now or later.

Banks, retailers and logistics firms use it for real-time fraud checks, stock updates and tracking, and to feed data platforms. Running it yourself is demanding, so many choose a managed service.

Names you'll meet

  • Apache Kafka
  • Confluent
  • Amazon MSK
  • Azure Event Hubs
  • RabbitMQ

What's inside

  1. 1

    Topics & partitions

    Named streams of events, split up for parallel processing.

  2. 2

    Producers & consumers

    Apps that write events and apps that read them.

  3. 3

    Kafka Connect

    Ready-made connectors to databases, SaaS apps and storage.

  4. 4

    Stream processing

    Kafka Streams or Apache Flink transform events as they flow.

Is it right for you?

Best for

  • Real-time use cases: fraud, pricing, tracking, IoT
  • Feeding many downstream systems from one source of change
  • Very high message volumes

Think twice if…

  • Your integrations are simple request-and-response; an API or iPaaS is easier
  • Volumes are low; a message queue such as RabbitMQ is enough

Typical projects

  1. Event streaming platform setup6–14 weeks
  2. Change data capture from core databases6–16 weeks
  3. Real-time analytics use case8–20 weeks

Typical ranges, not quotes. Scope, data and team size move them most.

Roles you'll hire

  • Streaming / data engineer
  • Kafka platform engineer
  • Solution architect
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Questions to ask a vendor

  1. 1Self-managed, Confluent Cloud or our cloud's own service: which, and why?
  2. 2How will you design topics, schemas and retention?
  3. 3How do you monitor consumer lag and recover from failures?
  4. 4Have you run Kafka at our volume?

Find Kafka partners

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