PhoenixAI Joins Cloudera as a Foundational Database Partner

PhoenixAI Cloud database engine to be available on Cloudera Anywhere Cloud ™ Marketplace, bringing sub-second real-time analytics and agentic AI workloads to Cloudera’s user base.

PhoenixAI, the Agentic AI Database, announced a strategic partnership with Cloudera, the only company bringing AI to data anywhere. PhoenixAI is joining as a foundational data partner for Cloudera’s newly launched hybrid data and AI platform, and Cloudera Anywhere Cloud Marketplace. Through this partnership, enterprise customers can deploy PhoenixAI’s high-performance cloud database engine directly within Cloudera’s secure private and public cloud environments.

As organizations accelerate their adoption of autonomous AI agents and real-time decision-making systems, access to fresh, sub-second enterprise data is critical. PhoenixAI’s inclusion in Cloudera’s private and sovereign infrastructure offering delivers an AI-native database foundation designed specifically for high-concurrency, low-latency workloads while adhering to strict enterprise governance and data sovereignty mandates.

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Speed, Reduced Complexity, and Enhanced Security

By making PhoenixAI natively available within Cloudera’s ecosystem, the joint solution delivers three core advantages to enterprise engineering and data teams:

Sub-Second Speed at Scale: PhoenixAI delivers sub-second SQL query performance across live streaming data and historical lakehouse formats, sustaining high concurrency without performance degradation.

Radically Reduced Complexity: Customers can instantly spin up a managed database cluster in a couple of clicks via the Cloudera Anywhere Cloud Marketplace. PhoenixAI queries real-time and lakehouse data in place—eliminating mandatory data denormalization, complex pre-aggregations, or unnecessary ETL pipelines.

Enhanced Security and Enterprise Trust: Deployed securely within the customer’s private cloud environment, PhoenixAI enforces fine-grained role-based access control (RBAC), per-query auditing, and full data sovereignty, ensuring sensitive AI workloads remain protected under enterprise security protocols.