Introducing Husky, Datadog’s third-generation event store | Datadog

This post details the evolution of Datadog's event store, introducing 'Husky' as the third-generation system. It describes the limitations of previous iterations, particularly the challenges of multi-tenant clusters and the need for independent compute and storage. Husky's design focuses on owning the storage engine from top to bottom, inspired by systems like Snowflake. Key architectural decisions include separating compute from storage to scale ingestion, storage, and query paths independently, and enabling product teams to query and aggregate on any field without pre-defined indexing. The system aims to support critical data retention for longer periods, handle array and windowing functions, and directly store DDSketches for re-aggregation at query time.
More from the Husky Query Engine trail
- Inside Husky’s query engine: Real-time access to 100 trillion events | Datadog
- Husky: Efficient compaction at Datadog scale | Datadog
- Timeseries indexing at scale | Datadog
- Making fetch happen: Building a general-purpose query and render scheduler | Datadog
- Husky: Exactly-once ingestion and multi-tenancy at scale | Datadog