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

Cloudera DataFlow vs Confluent comparison

 

Comparison Buyer's Guide

Executive SummaryUpdated on Dec 17, 2024

Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Categories and Ranking

Cloudera DataFlow
Ranking in Streaming Analytics
15th
Average Rating
7.4
Reviews Sentiment
6.5
Number of Reviews
5
Ranking in other categories
No ranking in other categories
Confluent
Ranking in Streaming Analytics
4th
Average Rating
8.2
Reviews Sentiment
6.7
Number of Reviews
23
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of July 2025, in the Streaming Analytics category, the mindshare of Cloudera DataFlow is 1.2%, down from 1.4% compared to the previous year. The mindshare of Confluent is 8.3%, down from 10.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

Mohamed-Saied - PeerSpot reviewer
Efficient data integration and workflow scheduling elevate project performance
Cloudera DataFlow is used as an ETL or ELT solution within Cloudera's data pipeline. Our organization heavily relies on it for data ingestion, transformation, and warehousing. It is also used daily for operational tasks, and it integrates well within Cloudera's ecosystem for high performance and…
Gustavo-Barbosa Dos Santos - PeerSpot reviewer
Has good technical support services and a valuable feature for real-time data streaming
Implementing Confluent's schema registry has significantly enhanced our organization's data quality assurance. It helps us understand the various requirements of multiple customers and validates the information for different versions. We can automate the tasks using Confluent Kafka. Thus, it guarantees us the data quality and maintains the integrity of message contracts.

Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:
 

Pros

"Cloudera DataFlow is fully compatible with Cloudera's ecosystem and offers high efficiency through native connectors for various ecosystems."
"This solution is very scalable and robust."
"The initial setup was not so difficult"
"DataFlow's performance is okay."
"The most effective features are data management and analytics."
"The client APIs are the most valuable feature."
"We mostly use the solution's message queues and event-driven architecture."
"The documentation process is fast with the tool."
"Our main goal is to validate whether we can build a scalable and cost-efficient way to replicate data from these various sources."
"I find Confluent's Kafka Connectors and Kafka Streams invaluable for my use cases because they simplify real-time data processing and ETL tasks by providing reliable, pre-packaged connectors and tools."
"Kafka Connect framework is valuable for connecting to the various source systems where code doesn't need to be written."
"A person with a good IT background and HTML will not have any trouble with Confluent."
"The benefit is escaping email communication. Sometimes people ignore emails or put them into spam, but with Confluence, everyone sees the same text at the same time."
 

Cons

"It's an outdated legacy product that doesn't meet the needs of modern data analysts and scientists."
"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."
"Although their workflow is pretty neat, it still requires a lot of transformation coding; especially when it comes to Python and other demanding programming languages."
"It could be improved by including a feature that automatically creates a new topic and puts failed messages."
"Confluent's price needs improvement."
"Confluence could improve the server version of the solution. However, most companies are going to the cloud."
"They should remove Zookeeper because of security issues."
"It could have more integration with different platforms."
"It could be more user-friendly and centralized. A way to reduce redundancy would be helpful."
"Areas for improvement include implementing multi-storage support to differentiate between database stores based on data age and optimizing storage costs."
"One area we've identified that could be improved is the governance and access control to the Kafka topics. We've found some limitations, like a threshold of 10,000 rules per cluster, that make it challenging to manage access at scale if we have many different data sources."
 

Pricing and Cost Advice

"DataFlow isn't expensive, but its value for money isn't great."
"Confluence's pricing is quite reasonable, with a cost of around $10 per user that decreases as the number of users increases. Additionally, it's worth noting that for teams of up to 10 users, the solution is completely free."
"You have to pay additional for one or two features."
"On a scale from one to ten, where one is low pricing and ten is high pricing, I would rate Confluent's pricing at five. I have not encountered any additional costs."
"Confluent is expensive, I would prefer, Apache Kafka over Confluent because of the high cost of maintenance."
"Confluent has a yearly license, which is a bit high because it's on a per-user basis."
"The pricing model of Confluent could improve because if you have a classic use case where you're going to use all the features there is no plan to reduce the features. You should be able to pick and choose basic services at a reduced price. The pricing was high for our needs. We should not have to pay for features we do not use."
"It comes with a high cost."
"Confluent is an expensive solution."
report
Use our free recommendation engine to learn which Streaming Analytics solutions are best for your needs.
860,592 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
University
16%
Financial Services Firm
15%
Computer Software Company
13%
Retailer
7%
Financial Services Firm
18%
Computer Software Company
16%
Manufacturing Company
6%
Insurance Company
5%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Cloudera DataFlow?
The most effective features are data management and analytics.
What needs improvement with Cloudera DataFlow?
Cloudera DataFlow's UI interface could be enhanced significantly. Memory handling can also be improved to be better than it is today.
What is your primary use case for Cloudera DataFlow?
Cloudera DataFlow is used as an ETL or ELT solution within Cloudera's data pipeline. Our organization heavily relies on it for data ingestion, transformation, and warehousing. It is also used daily...
What do you like most about Confluent?
I find Confluent's Kafka Connectors and Kafka Streams invaluable for my use cases because they simplify real-time data processing and ETL tasks by providing reliable, pre-packaged connectors and to...
What is your experience regarding pricing and costs for Confluent?
They charge a lot for scaling, which makes it expensive.
What needs improvement with Confluent?
I am not very impressed by Confluent. We continuously face issues, such as Kafka being down and slow responses from the support team. The lack of easy access to the Confluent support team is also a...
 

Comparisons

 

Also Known As

CDF, Hortonworks DataFlow, HDF
No data available
 

Overview

 

Sample Customers

Clearsense
ING, Priceline.com, Nordea, Target, RBC, Tivo, Capital One, Chartboost
Find out what your peers are saying about Cloudera DataFlow vs. Confluent and other solutions. Updated: June 2025.
860,592 professionals have used our research since 2012.