Customer-Facing Analytics
Building embedded analytics into your product means serving thousands of users, each with their own data, simultaneously. PhoenixAI is built for exactly this — multi-tenant, sub-second, at any scale.
<1s
Dashboard load time
Coinbase production (down from 8 seconds)
10K+
Concurrent users
Sustained QPS
3×
Cost-performance gain
Replacing Apache Druid at Pinterest
The problem
What breaks at scale
With PhoenixAI
Capabilities
The features that matter when analytics is a core part of your product.
Maintain consistent dashboard load times whether you have 100 or 100,000 concurrent users. PhoenixAI’s architecture doesn’t degrade under load.
Cell-level security enforces tenant data boundaries at query execution time. Multi-warehouse design adds hard compute isolation so noisy tenants can’t starve quiet ones.
Your customers see data that’s seconds old, not hours. Event streams feed directly into the query layer — no ETL delay between action and insight.
Standard JDBC/ODBC, REST API, and MySQL-compatible wire protocol. Integrate PhoenixAI into your application stack without changing your query patterns.
PhoenixAI connects to the tools product engineering teams already use for data pipelines, embedding, and visualization.
Data ingestion
Application integration
Embedded analytics
In production
“The migration reduced the p90 latency by 50% with only 32% of the instances required by the previous set up. This resulted in a 3-fold increase in cost-performance efficiency. The data ingestion process was also streamlined, achieving a data freshness of just 10 seconds.”
PhoenixAI customer
10s
data freshness