Cloudera

Name: Cloudera
Brand: Cloudera
Rating: 4.5 (735 reviews)

Cloudera is a hybrid data, analytics, and AI platform that runs across AWS, Azure, Google Cloud and on-prem environments, providing centralized management, governance (SDX with Ranger/Atlas), and services for data ingestion, data engineering, data warehousing, operational databases, and AI/ML tooling.

Est 2008|Valuation $4.7B|Raised $572.3M|99 Ref Customers

LinkedIn 300K|Web traffic 339K|FTEs 3,484|HQ Santa Clara, California, US

MarketsData Governance Data Warehouses & Lakehouses Data Catalog Data Science & Machine Learning Platforms Cloud Infrastructure Providers (IaaS/PaaS)

Platform CoversData Integration (ETL/ELT)

01Competitive Landscape

Narrative analysis

#### Cloudera vs Databricks - Where Cloudera tends to be selected: Organizations with hybrid or on‑prem requirements, needing governance consistency and management of Hadoop ecosystem components. - Where Databricks tends to be selected: Cloud‑native analytics and ML teams prioritizing a managed, integrated developer experience and faster iteration. #### Cloudera vs Snowflake (common alternative) - Snowflake is frequently selected when workloads are predominantly cloud based and teams prioritize a managed SQL warehouse experience. - Cloudera is often selected when partial on‑prem data retention, hybrid governance, or broader ecosystem tooling (streaming, operational databases) is required under a governance framework. #### Cloudera vs Starburst - Starburst is attractive for organizations that need cross‑source federation and transparent query pricing. - Cloudera is chosen when a broader operational platform is required for ingestion, streaming, and Hadoop‑native processing in addition to query capabilities.

Market adoption trends (high‑level)

Community discussions and vendor comparisons indicate that Cloudera remains present in regulated sectors and legacy deployments. Cloud modernization programs frequently evaluate or migrate toward Databricks, Snowflake, or cloud provider analytics services.

	Cloudera (CDP)	Databricks	Starburst
Starting price	Published usage‑based CCU rates for many services; infrastructure costs are separate	Usage‑based; pay‑as‑you‑go with published DBU rates; total cost depends on cloud/instance choices	Free tier available; paid plans with published credit pricing and tiered options
Primary use cases	Regulated enterprises requiring hybrid/on‑prem deployments, governance, and Hadoop ecosystem support	Cloud‑first analytics/ML teams seeking integrated notebooks, ML tooling, and elastic scaling	Federated analytics and Trino‑based query across multiple sources without large data movement
Key strengths	Support for hybrid deployments and governance architecture (SDX with Ranger/Atlas/Knox patterns) and broad ecosystem coverage	Integrated ML/analytics experience, managed cloud UX, and elastic scaling	SQL federation, transparency in consumption pricing for query compute, and Trino‑based openness
Key weaknesses	Platform complexity and potential operational burden; perceptions of proprietary components mixed with OSS	Potential for high cost without governance controls; less emphasis on on‑prem support	Not a drop‑in replacement for a full Hadoop distribution; may require additional platform components for some enterprise needs

01Competitive Landscape

Narrative analysis

Cloudera vs Databricks

Where Cloudera tends to be selected: Organizations with hybrid or on‑prem requirements, needing governance consistency and management of Hadoop ecosystem components.
Where Databricks tends to be selected: Cloud‑native analytics and ML teams prioritizing a managed, integrated developer experience and faster iteration.

Cloudera vs Snowflake (common alternative)

Snowflake is frequently selected when workloads are predominantly cloud based and teams prioritize a managed SQL warehouse experience.
Cloudera is often selected when partial on‑prem data retention, hybrid governance, or broader ecosystem tooling (streaming, operational databases) is required under a governance framework.

Cloudera vs Starburst

Starburst is attractive for organizations that need cross‑source federation and transparent query pricing.
Cloudera is chosen when a broader operational platform is required for ingestion, streaming, and Hadoop‑native processing in addition to query capabilities.

Market adoption trends (high‑level)

	Cloudera (CDP)	Databricks	Starburst
Starting price	Published usage‑based CCU rates for many services; infrastructure costs are separate	Usage‑based; pay‑as‑you‑go with published DBU rates; total cost depends on cloud/instance choices	Free tier available; paid plans with published credit pricing and tiered options
Primary use cases	Regulated enterprises requiring hybrid/on‑prem deployments, governance, and Hadoop ecosystem support	Cloud‑first analytics/ML teams seeking integrated notebooks, ML tooling, and elastic scaling	Federated analytics and Trino‑based query across multiple sources without large data movement
Key strengths	Support for hybrid deployments and governance architecture (SDX with Ranger/Atlas/Knox patterns) and broad ecosystem coverage	Integrated ML/analytics experience, managed cloud UX, and elastic scaling	SQL federation, transparency in consumption pricing for query compute, and Trino‑based openness
Key weaknesses	Platform complexity and potential operational burden; perceptions of proprietary components mixed with OSS	Potential for high cost without governance controls; less emphasis on on‑prem support	Not a drop‑in replacement for a full Hadoop distribution; may require additional platform components for some enterprise needs