The hybrid data cloud for the complete data lifecycle and Enterprise AI.
Cloudera Data Platform (CDP) is a comprehensive hybrid data cloud architecture designed for the 2026 enterprise landscape, where data resides across multi-cloud and on-premises environments. Built on an open-source core (Hadoop/Spark/Flink) and optimized with Apache Iceberg as the open table format, CDP enables a true 'Open Data Lakehouse.' Its primary technical differentiator is the Shared Data Experience (SDX), a unified security and governance layer that ensures consistent data privacy and compliance across all workloads. As of 2026, CDP has pivoted heavily toward 'Enterprise AI,' providing 'AI Accelerators' and containerized machine learning workspaces (CML) that allow organizations to build, deploy, and monitor LLMs and generative AI applications securely. The platform manages the entire lifecycle from real-time data ingestion via Apache NiFi to advanced analytics and long-term cold storage using Apache Ozone. It is positioned as the high-scale alternative to Snowflake and Databricks for organizations requiring strict data sovereignty and hybrid flexibility.
Centralized security and governance for all data across the platform using Apache Ranger and Atlas.
The unified, AI-powered data platform that centralizes organizational intelligence for agentic workflows.
The Universal Semantic Layer for AI and Data Applications.
Autonomous Event Orchestration and Semantic Data Synchronization for Distributed Systems.
The Universal Semantic Layer for Modern Data Applications and AI.
Verified feedback from the global deployment network.
Post queries, share implementation strategies, and help other users.
Native support for the Iceberg table format for high-performance ACID transactions on object stores.
Containerized ML platform supporting R, Python, and Scala with integrated LLM blueprints.
A cloud-native NiFi-based streaming service for edge-to-cloud data ingestion.
Automated data and metadata movement between different CDP clusters (Public or Private).
Scalable, redundant, and distributed object store optimized for Hadoop workloads.
The ability to scale compute clusters up or down without disrupting running queries.
Identifying fraudulent credit card transactions in milliseconds across global regions.
Registry Updated:2/7/2026
Update ML model in CML.
Moving sensitive PII data from on-prem to AWS while maintaining audit trails.
Building a RAG (Retrieval-Augmented Generation) system using internal documentation.