How to design a real-time event architecture using Apache Kafka or AWS Kinesis?

To build a real-time event architecture:

  1. Ingest Events: Use Snowplow trackers to collect events from web, mobile, or IoT sources.
  2. Stream Events: Forward data to a streaming platform like Kafka or AWS Kinesis for reliable and scalable transport.

  3. Process Events: Apply transformations or analytics in real time using tools like Apache Flink, Spark Streaming, or AWS Lambda.
  4. Route Processed Data: Send output to data warehouses (e.g., Snowflake), dashboards, or real-time inference engines.

This architecture enables low-latency data flow, making it suitable for dynamic, responsive applications.

Learn How Builders Are Shaping the Future with Snowplow

From success stories and architecture deep dives to live events and AI trends — explore resources to help you design smarter data products and stay ahead of what’s next.

Browse our Latest Blog Posts
Upcoming Webinar

Building the Real-Time Foundation for AI-Powered Customer Experiences

Video

CDO Magazine Interview with Kalyani Sekar

Webinar

Reimagining Data Governance for Faster Business Outcomes

Upcoming Webinar

How Engel & Völkers Powers Smarter Content with Behavioral Data

Webinar

TDWI Tech-In-Action: Overcoming Challenges with Behavioral Data Pipelines

Get Started

Whether you’re modernizing your customer data infrastructure or building AI-powered applications, Snowplow helps eliminate engineering complexity so you can focus on delivering smarter customer experiences.

Book a DemoWatch our 10-min Demo