Joins on normalized schemas
Multi-table joins run directly on normalized schemas, often in under a second, without flattening data into wide tables first.
StarRocks and PhoenixAI
PhoenixAI created StarRocks and still leads its development. PhoenixAI extends the StarRocks engine and adds row and column access policies, workload isolation, multi-AZ high availability, and 24/7 support with an SLA. It stays compatible with open-source StarRocks, so your SQL and schemas carry over.
Trusted by teams running StarRocks in production
New to StarRocks?
StarRocks is the open-source real-time analytical database created by PhoenixAI.
Multi-table joins run directly on normalized schemas, often in under a second, without flattening data into wide tables first.
Data from Kafka or Flink CDC is queryable within seconds, including updates and deletes.
Reads Iceberg, Delta Lake, and Hive tables without copying them. It uses the MySQL wire protocol, so MySQL-compatible BI tools and drivers connect without changes.
Already running StarRocks?
Open-source StarRocks gives you the core query engine. Teams running it in production usually also need row and column access policies, Kerberos and SSO, separate compute for agents and BI, multi-AZ availability, and automated upgrades. PhoenixAI includes all of these.
Open-source StarRocks
PhoenixAI
The feature gap
| Capability | PhoenixAI | StarRocks (open source) |
|---|---|---|
| Core engine | The StarRocks engine with PhoenixAI enhancements, compatible with open-source SQL, schemas, and connectors. | The open-source StarRocks engine. |
| Access control | Native row access and column masking policies, applied at query time. | RBAC and column privileges. Row and masking policies only through an external Apache Ranger deployment. |
| Authentication and encryption | Kerberos, LDAP, and SSO from the console. Transparent data encryption. Vulnerability management. | Native, LDAP, OAuth 2.0, and JWT, configured by hand. Kerberos and encryption at rest are not available. |
| Workload isolation | Multi-warehouse: agents, BI, and ETL each get their own compute, with autoscaling. | Resource groups share one pool of compute inside a cluster. |
| High availability | Multi-AZ, cache high availability with automatic warmup, cross-cluster replication. | Replicas inside a single cluster. |
| Operations | Automated upgrades, patching, backups, and failure recovery. Console with monitoring, alerting, and graphical query profiling. | Upgrades and backups are manual. Metrics endpoints; you build the dashboards. |
| Lakehouse and materialized views | Unity Catalog, Iceberg V3, incremental materialized views, automatic MV recommendation. | Iceberg V2, Delta Lake, Hive. Async materialized views with scheduled refresh; no incremental refresh or MV recommendation. |
| Support and compliance | 24/7 support with an SLA from the engineers who write StarRocks. SOC 2 Type 2 and GDPR. | Community Slack and GitHub issues. |
Two ways to run it
Both include the same enterprise features, such as multi-warehouse isolation that gives agents, BI, and ETL their own compute. The difference is who operates the platform and where it can run.
Runs in your AWS, Azure, or Google Cloud account. PhoenixAI handles deployment, upgrades, and monitoring, and your data stays in your account.
Your platform team runs the whole platform, control plane included, with our Kubernetes operator. It works in a cloud VPC, your own data center, or an air-gapped network, and licenses validate offline.
Open source and commercial
Yes. StarRocks is a Linux Foundation project under the Apache 2.0 license.
In the docs. The PhoenixAI Cloud and PhoenixAI Anywhere pages each have a table comparing every capability with open-source StarRocks.
PhoenixAI is built on open-source StarRocks and adds commercial features on top. It stays compatible with open-source StarRocks, so your SQL, schemas, and tools carry over, and you are not tied to a proprietary system.
Yes. PhoenixAI Anywhere runs in your cloud account or data center with full, allowlisted, or no outbound connectivity.