Try our new research platform with insights from 80,000+ expert users
Cloudera DataFlow Logo

Cloudera DataFlow Reviews

Vendor: Cloudera
3.7 out of 5
Leave a review

What is Cloudera DataFlow?

Cloudera DataFlow (CDF) is a comprehensive edge-to-cloud real-time streaming data platform that gathers, curates, and analyzes data to provide customers with useful insight for immediately actionable intelligence. It resolves issues with real-time stream processing, streaming analytics, data provenance, and data ingestion from IoT devices and other sources that are associated with data in motion. Cloudera DataFlow enables secure and controlled data intake, data transformation, and content routing because it is built entirely on open-source technologies. With regard to all of your strategic digital projects, Cloudera DataFlow enables you to provide a superior customer experience, increase operational effectiveness, and maintain a competitive edge.

Get the Streaming Analytics Buyer's Guide and find out what your peers are saying about Cloudera DataFlow, Databricks, Confluent and more!
Cloudera DataFlow is the #16 ranked solution in Streaming Analytics tools. PeerSpot users give Cloudera DataFlow an average rating of 7.4 out of 10. Cloudera DataFlow is most commonly compared to Databricks: Cloudera DataFlow vs Databricks. Cloudera DataFlow is popular among the large enterprise segment, accounting for 66% of users researching this solution on PeerSpot. The top industry researching this solution are professionals from a university, accounting for 20% of all views.
Buyer's Guide
Streaming Analytics
August 2025
Get the category report
Helped 865,985 peers since 2012

Featured Cloudera DataFlow reviews

Read more reviews

Cloudera DataFlow mindshare

As of August 2025, the mindshare of Cloudera DataFlow in the Streaming Analytics category stands at 1.1%, down from 1.3% compared to the previous year, according to calculations based on PeerSpot user engagement data.
Streaming Analytics Market Share Distribution
ProductMarket Share (%)
Cloudera DataFlow1.1%
Apache Flink14.5%
Databricks13.5%
Other70.9%
Streaming Analytics
 
 
Key learnings from peers

Valuable Features

Cloudera DataFlow offers scalability and robust performance. Users value its minimal coding requirement and effective data management and analytics. Its native connectivity with Cloudera ecosystems like Hive, Impala, and Spark ensures high performance. The platform allows end-to-end workflow scheduling without third-party apps.
  • "Cloudera DataFlow is fully compatible with Cloudera's ecosystem and offers high efficiency through native connectors for various ecosystems."
  • "The most effective features are data management and analytics."
  • "The initial setup was not so difficult"

Room for Improvement

Cloudera DataFlow requires less transformation coding, especially for Python, and a more open environment for external data interaction. Users find it challenging to use the R language effectively and note that the setup process could be simplified. The UI interface needs enhancement, and memory handling should be more efficient.
  • "Cloudera DataFlow's UI interface could be enhanced significantly. Memory handling can also be improved to be better than it is today."
  • "It is not easy to use the R language. Though I don't know if it's possible, I believe it is possible, but it is not the best language for machine learning."
  • "It's an outdated legacy product that doesn't meet the needs of modern data analysts and scientists."

Pricing

  • "DataFlow isn't expensive, but its value for money isn't great."

Popular Use Cases

Cloudera DataFlow is primarily used for sentiment analysis, fraud detection, and product royalty analysis. Entities also rely on it for creating quality modules tailored to telecommunication companies. It supports stream analytics and serves as an ETL or ELT tool within Cloudera's data pipeline, essential for data ingestion, transformation, and warehousing. Daily operational tasks benefit from its integration within Cloudera's ecosystem, offering high performance and throughput.

Service and Support

Cloudera DataFlow customer service and support is rated well, with users noting responsiveness and expertise. While responses can sometimes be delayed, satisfaction is generally high with first and second-level support access. Some turn to online sources for immediate assistance. Overall, users give it an eight out of ten for its effectiveness and knowledgeable staff.

Scalability

Cloudera DataFlow demonstrates strong scalability, handling high volumes of events efficiently. While it can manage large data sizes, extending its capacity may require technical expertise and has some limitations. Users have expressed varying satisfaction levels, with some rating it highly for scalability, while others suggest the need for further enhancements.
These insights are based on the in-depth reviews provided by peers to help you make a better buying decision.
Download our Streaming Analytics Buyer's Guide for additional reliable information.

Top industries

By visitors reading reviews
University
20%
Computer Software Company
13%
Financial Services Firm
12%
Retailer
9%
Performing Arts
8%
Media Company
7%
Healthcare Company
5%
Comms Service Provider
4%
Manufacturing Company
3%
Educational Organization
3%
Government
3%
Wholesaler/Distributor
1%
Construction Company
1%
Hospitality Company
1%
Insurance Company
1%
Logistics Company
1%
Non Profit
1%
Pharma/Biotech Company
1%
Real Estate/Law Firm
1%
Security Firm
1%
Transportation Company
1%
Leisure / Travel Company
1%

Compare Cloudera DataFlow with alternative products

Go!

Learn more about Cloudera DataFlow

With Cloudera DataFlow, you can take the next step in modernizing your data streams by connecting your on-premises flow management, streams messaging, and stream processing and analytics capabilities to the public cloud.

Cloudera DataFlow Advantage Features

Cloudera DataFlow has many valuable key features. Some of the most useful ones include:

  • Edge and flow management: Edge agents and an edge management hub work together to provide the edge management capability. Edge agents can be managed, controlled, and watched over in order to gather information from edge hardware and push intelligence back to the edge. Thousands of edge devices can now be used to design, deploy, run, and monitor edge flow apps. Edge Flow Manager (EFM) is an agent management hub that enables the development, deployment, and monitoring of edge flows on thousands of MiNiFi agents using a graphical flow-based programming model.
  • Streams messaging: The CDF platform guarantees that all ingested data streams can be temporarily buffered so that other applications can use the data as needed. This makes it possible for a business to scale efficiently, as data streams from thousands of origination points start to grow to petabyte sizes. To achieve IoT-scale, streams messaging allows you to buffer large data streams using a publish-subscribe strategy.
  • Stream analytics and processing: The third tenet of the CDF platform is its capacity to analyze incoming data streams in real time and with minimal latency, providing actionable intelligence in the form of predictive and prescriptive insights. This stage is essential to completing the Data-in-Motion lifecycle for an enterprise because there is only a use in absorbing all real-time streams if something useful is done with them in the moment to benefit your company.
  • Shared Data Experience (SDX): The most crucial component that transforms CDF into a genuine platform is Cloudera Data Platform's SDX. It is a powerful data fabric that offers the broadest possible deployment flexibility and guarantees total security, governance, and control across infrastructures. You get a single experience for security (with Apache Ranger), governance (with Apache Atlas), and data lineage from edge to cloud because all the CDF components seamlessly connect with SDX.

Cloudera DataFlow Advantage Benefits

There are many benefits to implementing Cloudera DataFlow . Some of the biggest advantages the solution offers include:

  • Completely open source: Invest in your architecture with confidence, knowing that there will be no vendor lock-in.
  • More than 300 pre-built processors: This is the only product that provides edge-to-cloud connection this comprehensive as well as a no-code user experience
  • Integrated data provenance: The market's only platform that offers out-of-the-box, end-to-end data lineage tracking and provenance across MiNiFi, NiFi, Kafka, Flink, and more.
  • Multiple stream processing engines to choose from: Supports Spark structured streaming, Kafka Streams, and Apache Flink for real-time insights and predictive analytics.
  • Hundred of Kafka consumers: Cloudera has hundreds of satisfied customers who receive exceptional support for their complex Kafka implementations.
  • Use cases for edge IoT: IoT data from thousands of endpoints may be easily collected, processed, and managed from the edge to the cloud with a multi-cloud/hybrid cloud strategy.
  • Hybrid/multi-cloud approach: Choose a flexible deployment option for your streaming architecture that spans across edge, on-premises, and various cloud environments with ease thanks to the power of CDP.

Cloudera DataFlow was previously known as CDF, Hortonworks DataFlow, HDF.

Cloudera DataFlow customers

Clearsense

Related questions

  • 33
How do you select the right cloud ETL tool?
  • 22
What is the best streaming analytics tool?
  • 44
What are the benefits of streaming analytics tools?
  • 55
What features do you look for in a streaming analytics tool?
  • 12
When evaluating Streaming Analytics, what aspect do you think is the most important to look for?
  • 15
Why is Streaming Analytics important for companies?

Product Categories

Product Categories
Streaming Analytics

Popular Comparisons

Popular Comparisons
Databricks vs Cloudera DataFlow Logo
Databricks vs Cloudera DataFlow
Confluent vs Cloudera DataFlow Logo
Confluent vs Cloudera DataFlow
Spring Cloud Data Flow vs Cloudera DataFlow Logo
Spring Cloud Data Flow vs Cloudera DataFlow
Amazon MSK vs Cloudera DataFlow Logo
Amazon MSK vs Cloudera DataFlow
Starburst Enterprise vs Cloudera DataFlow Logo
Starburst Enterprise vs Cloudera DataFlow
Informatica Data Engineering Streaming vs Cloudera DataFlow Logo
Informatica Data Engineering Streaming vs Cloudera DataFlow
Talend Data Streams vs Cloudera DataFlow Logo
Talend Data Streams vs Cloudera DataFlow
WSO2 Stream Processor vs Cloudera DataFlow Logo
WSO2 Stream Processor vs Cloudera DataFlow
See all alternatives
 
Cloudera DataFlow Reviews Summary
Author infoRatingReview Summary
Senior Data Architect at Teradata Corporation4.0I use Cloudera DataFlow as an ETL solution for data ingestion and transformation within Cloudera's ecosystem, appreciating its native connectivity with components like Hive and Spark. Although the UI and memory handling need improvement, its integration benefits outweigh alternatives like Informatica.
Consultant at a government with 10,001+ employees2.5I find Cloudera DataFlow's performance satisfactory. However, it feels restrictive as it requires keeping data within its closed environment, with no options for working with external virtual data. I haven't explored other solutions or cloud providers yet.
Manager at a tech services company with 201-500 employees4.0No summary available
CEO at AM-BITS LLC4.5I use Cloudera DataFlow primarily for stream analytics. The most effective features are data management and analytics, though I believe the setup process could be simpler. I haven't considered or used any alternative solutions or cloud providers.
Data Scientist at Orys3.5I use Cloudera DataFlow to develop quality modules for telecommunication companies. I utilize all features for data analysis, though not machine learning. Improvement is needed in using the R language as it's challenging and not ideal for machine learning.