Jordan Thoms, CTO and Co-Founder at Kami
Kami's in-house analytics system collects clickstream data for 45 million users, reaching 300 GB per day and over 200 billion total data points. This data, ingested into the company’s data warehouse, informs key business decisions, such as product roadmaps, sales planning, and marketing. With Kami’s explosive growth, we have successively rearchitected our data infrastructure to allow for massive scale. In this talk, Jordan will explain how user activity data from Kami’s web app moves through Ruby on Rails, Sidekiq, Kafka, and an in-house Kafka consumer before real-time ingestion into ClickHouse.


Introduction to ClickHouse - Auckland Meetup
Johnny Mirza, Solution Architect at ClickHouse


How to Leverage ClickHouse Vector Search Capabilities for Merchant Matching at Ramp
Peyton McCullough, Ramp Anton Biryukov, Ramp


ClickStream Ingestion 101 with Jitsu
Vladimir Klimontovich, Jitsu