01
Real-Time AI-Ready
Analytics for the Agent Era
Apache Doris gives AI applications real-time access to trusted, queryable enterprise data. Build data-aware agents, improve RAG quality, monitor AI behavior, and run analytics and hybrid search across structured, semi-structured, and unstructured data at scale.
Why AI-readyanalytics matters forthe agent era.
When the analytical foundation is fresh, hybrid, observable, and unified, five things shift at once:
- Decision quality
- Application context
- Retrieval relevance
- Agent visibility
- The cost of running it all
Real-Time AI Decisions
AI agents query live operational data and act while the user interaction or business process is still in progress.
Data-Aware Applications
Copilots, agents, and RAG systems draw on fresh, trusted enterprise data for context, memory, and reliable actions.
RAG & Knowledge Retrieval
SQL filters, full-text search, BM25, and vector search run in one query, so LLMs get accurate context and hallucinate less.
AI Observability
Prompts, responses, traces, tool calls, token usage, and cost sit in one queryable store for debugging and ongoing quality control.
Simplified AI Data Stack
One engine covers real-time analytics, full-text and vector search, log analysis, and AI-native SQL, with fewer pipelines to run.
What AI-ready analytics demandsand how Apache Doris answers.
Five things an AI-ready analytics platform has to do well, and the specific Apache Doris capabilities that meet each one.
Apache Doris capabilities for AI
Each capability links to its feature doc. For the engineering detail behind them, read the Apache Doris blog.
Real-Time Ingestion &
02
AI Observability for Prompts,
Traces, Cost & Quality
03
Flexible JSON Analytics
with VARIANT
04
Hybrid Search Across
SQL, Text & Vectors
05
