Features
Real-time analytical queries on petabytes of data
Column-oriented storage with high compression ratios
Distributed query execution across clusters
Cascading refreshable materialized views (26.6)
Hypothetical skip indexes for query optimization (26.6)
Experimental continuous queries for streaming (26.6)
Built-in vector search for AI/ML workloads
Separate compute and storage scaling
Auto-scaling to zero on idle (Cloud)
Over 100 native integrations via ClickPipes
Open-source (Apache 2.0) with managed cloud option
Time-series functions and window functions
Support for semi-structured data (JSON, arrays)
Role-based access control and data masking
LLM observability via Langfuse integration
Trace visibility for agent steps (prompts, retrievals, tool calls, outputs)
LLM-as-judge evaluation for relevance, toxicity, quality scoring
Dataset creation from traces for reproducible testing
Experiment management and regression benchmarking
Built-in Prompt IDE for iterative prompt optimization
Self-hosted deployment on local, Docker, Kubernetes
Phoenix Cloud managed hosting option
Vendor-agnostic support for any model/framework
Native OpenTelemetry integration
OpenInference specification for LLM telemetry
Human annotation and automated labeling
Ghost trajectories to simulate alternative agent paths
Eval-as-you-test for early quality feedback
One-click integration with LlamaIndex
