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
Distributed tracing for LLM agents
Capture prompts, retrievals, tool calls, outputs
Human annotations on traces
Create datasets from traces
Run experiments to compare changes
OpenTelemetry-native instrumentation
Self-host locally, Docker, or Kubernetes
Cloud instances with free tier
Vendor agnostic: any model or framework
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