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Cloudera was acquired by Clayton, Dubilier & Rice / KKR.
Brief
Cloudera

Cloudera

Cloudera provides a unified hybrid data platform that enables enterprises to manage, analyze, and derive AI-driven insights from data across any cloud or on-premises environment with enterprise-grade security and governance.

cloudera.comSanta Clara, California, United StatesFounded 2008

Last updated May 11, 2026 by ATDb automated enrichment · Connections updated May 25, 2026

Industry
Data Management & Analytics Infrastructure
Business Model
SaaS / Subscription
Target Market
Enterprise
Employee Count
1001-5000
Funding
$5.3B (take-private acquisition by CD&R and KKR in 2021)
Revenue Range
$800M - $1B
Parent Company
Clayton, Dubilier & Rice / KKR
API Available
Yes
Market Position

Leading hybrid cloud data platform provider for enterprise-scale data management, analytics, and AI workloads

Overview

Cloudera is an enterprise technology company that provides a unified data platform for data management, analytics, machine learning, and AI workloads across hybrid and multi-cloud environments. Originally founded as a pioneer in enterprise Hadoop-based big data solutions, Cloudera has evolved into a comprehensive data platform provider, offering tools that enable organizations to collect, store, process, and analyze massive volumes of data regardless of where it resides — on-premises, in the cloud, or at the edge. The company's Cloudera Data Platform (CDP) is its flagship offering, designed to give enterprises a consistent experience across public clouds and private infrastructure. Cloudera was formed through the 2018 merger of Cloudera and Hortonworks, two of the most prominent players in the enterprise Hadoop ecosystem, creating a dominant force in the big data market. In 2021, the company was taken private in a $5.3 billion acquisition by private equity firms Clayton, Dubilier & Rice and KKR, delisting from the NYSE. This transition allowed Cloudera to refocus its strategy around hybrid cloud data management and AI-driven analytics without the pressures of public market scrutiny. In the broader data and AdTech ecosystem, Cloudera serves as critical infrastructure for enterprises that need to process and analyze large-scale data for audience intelligence, customer data platforms, and marketing analytics. Its platform supports data governance, security, and compliance capabilities that are increasingly important in a privacy-first advertising landscape. Cloudera competes with cloud-native data platforms from major hyperscalers as well as specialized data warehouse and lakehouse vendors, positioning itself as the preferred choice for enterprises requiring hybrid flexibility and robust data governance.

Products & Features

Cloudera Data Platform (CDP)

Unified hybrid cloud platform for data management, analytics, and AI across public cloud and private cloud environments

CDP Public Cloud

Cloud-native data services on AWS, Azure, and Google Cloud for analytics and machine learning workloads

CDP Private Cloud

On-premises deployment of Cloudera's data platform for organizations with strict data residency requirements

Cloudera Data Warehouse

Self-service analytics and SQL-based data warehousing service optimized for large-scale enterprise queries

Cloudera Machine Learning (CML)

End-to-end machine learning platform for building, training, and deploying ML models at scale

Cloudera DataFlow (CDF)

Real-time streaming data ingestion and flow management powered by Apache NiFi

Cloudera Data Engineering (CDE)

Managed Apache Spark service for large-scale batch data engineering pipelines

Cloudera SDX (Shared Data Experience)

Centralized security, governance, and metadata management layer shared across all CDP services

Cloudera Replication Manager

Tool for migrating and replicating data across on-premises and cloud environments

Cloudera Observability

Monitoring and optimization service for data pipelines and workloads across the CDP ecosystem

Key Features
Hybrid and multi-cloud data managementUnified security and governance via SDXReal-time data streaming and ingestionEnterprise-grade machine learning and AIApache open-source ecosystem integration (Spark, Kafka, Hive, Impala, NiFi)Data lakehouse architecture supportAutomated data lifecycle managementRole-based access control and data maskingMulti-function analytics (SQL, ML, streaming, batch)Data catalog and lineage tracking
Use Cases
Enterprise data lakehouse and data warehouse modernizationCustomer 360 and audience intelligence for marketing analyticsReal-time streaming analytics for fraud detection and personalizationMachine learning model development and deployment at scaleData governance and compliance for GDPR/CCPA regulated dataAdTech data pipeline management and audience segmentationIoT and edge data processingFinancial risk analytics and reportingHealthcare data management and clinical analyticsSupply chain optimization and operational analytics
Customer Segments
Large enterprises in financial services and bankingHealthcare and life sciences organizationsTelecommunications companiesGovernment and public sector agenciesRetail and e-commerce enterprisesMedia and advertising technology companiesEnergy and utilities firmsManufacturing and industrial enterprises
Connections

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