PhoenixAI enables you to gain instant insights into all your data, without the need for redundant ETL pipelines.
[Webinar Replay] How Conductor Builds Sub-Second Agentic Analytics at Scale
Conductor helps some of the world's biggest brands drive visibility across AI and traditional search — and as they scaled into agentic workflows, their data architecture had to evolve fast. Watch Conductor's data platform leaders walk through how PhoenixAI Cloud powers sub-second query performance, their architecture for interactive analytics and MCP, and a behind-the-scenes look at their OpenAI and Claude integration.
Watch the Recording
PhoenixAI delivers sub-second latency, highly efficient complex joins, and continuous real-time updates to power interactive dashboards, data applications, and AI agents. Engineered for the strictest customer-facing workloads, it maintains predictable P95/P99 latency while supporting millions of users and agents with far fewer compute resources.
Unify Real-Time, Lakehouse, and AI Analytics
in One Sub-Second Engine
Sub-Second By Default
Consistent sub-second latency, intelligent acceleration, and predictable p95/p99 performance across millions of queries.
Embrace On-The-Fly JOINs
Eliminate rigid and costly denormalization pipelines with fast on-the-fly JOIN performance at any scale.
Faster Engineering Velocity
No data copy. No denormalization pipelines. Just a unified, AI-ready lakehouse that delivers faster engineering cycles and quicker insights.
Enterprise Analytics on Your Cloud
Full control, governance, and flexibility, built on open standards with no vendor lock-in.
Powered by StarRocks
We’re proud to be powered by StarRocks, the world’s fastest open-source Lakehouse SQL engine. PhoenixAI works closely with StarRocks’ global community of contributors to continually improve this popular project to better serve the developer community and our enterprise customers.
Simplicity and Performance, Guaranteed
VS
StarRocks vs. Trino/Presto
Many Trino and Presto deployments hit a latency wall as queries and concurrency grow. StarRocks typically delivers 3–8× faster query performance with more consistent latencies, without the heavy tuning and engine limits teams run into with Trino/Presto.
VS
StarRocks vs. ClickHouse
ClickHouse is optimized for simple, append-only workloads, but scaling complex joins, updates, and high-concurrency queries often requires tradeoffs. StarRocks is built for sub-second analytics on rich, multi-table schemas and heterogeneous workloads, without those compromises.
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StarRocks vs. Apache Druid
Apache Druid’s denormalization and pre-aggregation requirements add cost and complexity. StarRocks delivers high performance, high concurrency, and flexible SQL on normalized data, without the operational overhead typically associated with a Druid-style stack.
PhoenixAI Is the
Industry's Leading Real-Time OLAP Solution
PhoenixAI meets the requirements of real-time analytics with second-level data freshness on mutable data. PhoenixAI's scalable on-the-fly JOINs performance enables you to ditch expensive real-time denormalization pipelines.
Trusted by Top Customers
FANATICS
PHOENIXAI CUSTOMER
"StarRocks is at the center of our real-time data analytics. We strive for quicker and easier insights into day to day operations. We chose StarRocks for its ability to upsert data in real-time, support for joins across large fact tables with very low latency, and the ability to serve and join native and external tables from the same cluster."
DEMANDBASE
PHOENIXAI CUSTOMER
"PhoenixAI made migrating off of ClickHouse possible, and they’ve been there for everything we’ve needed. From ensuring cluster performance and stability to optimizing queries and rolling out enhancements at a rapid pace, we see a bright future with PhoenixAI.”
PHOENIXAI CUSTOMER
"After this migration to StarRocks, we observed multiple improvements. 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."
No Matter Your Approach to Analytics, We Can Help
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