OpenSearchCon Europe 2025

In observability and analytics workloads, aggregation queries are fundamental but often become a performance bottleneck as OpenSearch aggregations scale linearly with document count, leading to unpredictable latencies and resource consumption.

This session presents a technical deep dive into how we improved performance of OpenSearch aggregations by implementing star tree index, a sophisticated multi-field indexing structure that delivers up to 100x faster aggregations while maintaining predictable query latencies.

We'll walk through the complete journey of implementing star tree index in OpenSearch, from initial design challenges to production ready feature development.

The presentation covers the technical architecture that enables pre-computing aggregations during indexing, the complex merge operations that maintain performance during segment merges, and the sophisticated query algorithms that leverage star nodes for efficient pruning.

Through real-world benchmarks from various analytical workloads, we'll demonstrate how star tree indexes achieve dramatic performance improvements while managing storage overhead to be less than 1% for typical use cases along with tradeoffs.