Case Study: Snowplow achieves real-time event analytics and sub-minute insights with Amazon Web Services

Snowplow - Customer Case Study

Snowplow Analytics is an open‑source event analytics platform that helps companies collect granular, customer‑ and event‑level data from web and mobile sources and load it into structured stores for advanced analysis. Originally built as a batch system, Snowplow faced a challenge: customers needed real‑time insights and decisioning (for use cases like ad targeting or product recommendations) rather than overnight results, and the platform had to scale to hundreds of millions or billions of events per day.

To solve this, Snowplow built a linearly scalable AWS pipeline (EC2, Elastic Beanstalk, S3, EMR, Redshift) and added Amazon Kinesis to stream raw events through an enrichment step into S3 and drip into Redshift. The change cut data latency from hours or a day to about two minutes, enabled real‑time feedback loops and immediate behavioral targeting, supported massive event volumes, simplified operations, attracted more open‑source contributors, and opened new markets such as digital advertising.

Snowplow

Alexander Dean

Founder