Who We Are

Our Story

The catalyst for Chaos was simple, but profound. We had spent decades designing, building, and inventing technology across large-scale distributed systems and databases. Over that journey, it became clear that something fundamental needed to change in how information is represented and analyzed. The reason was unavoidable: the tsunami of data being generated was outpacing Moore’s Law and the limits of existing computer science.

Our conclusion was that the prevailing data structures and algorithms used to store and access information inevitably lead to systems that are costly and complex, regardless of how components are assembled. The breakthrough came when we worked through how to fully index data for large-scale, high-performance, multi-model analytics without exploding the size of the data representation or relying on complex sharding strategies.

Those insights culminated in a new representation (effectively a new data format) designed for extreme compression without requiring massive compute. It supports multiple access models, including text search and relational analytics. It is purpose-built for pure cloud object storage, eliminating the need for block storage. It naturally handles complex and sparse schemas. And it is entirely stream-based, requiring no sharding, enabling a fundamentally new distributed architecture.

With this breakthrough and a shared conviction, we came together to build ChaosSearch: a next-generation data platform for massive-scale analytics, designed to be simple, cost-efficient, and fast.