Explore the architecture and implementation of Retriever, a custom-built distributed column store database, in this 43-minute Strange Loop Conference talk. Learn how Honeycomb addressed the challenges of understanding complex distributed systems in production by developing a low-latency, schemaless database inspired by Facebook's Scuba. Discover the design decisions behind Retriever, including its use of disk storage, efficient column-oriented storage model, and ability to handle multi-tenancy and cost constraints. Gain insights into the write and read paths, data model, storage format, distributed queries, and fault tolerance mechanisms. Understand how Retriever ingests events from Kafka, manages quotas, and handles failure recovery. Delve into the lessons learned from operating a hand-rolled database at production scale with paying customers, and see how it compares to other solutions for sub-second complex queries over large data volumes in real time.