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Cloudera DataFlow vs Databricks 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
14th
Average Rating
7.4
Reviews Sentiment
6.5
Number of Reviews
5
Ranking in other categories
No ranking in other categories
Databricks
Ranking in Streaming Analytics
1st
Average Rating
8.2
Reviews Sentiment
7.0
Number of Reviews
88
Ranking in other categories
Cloud Data Warehouse (7th), Data Science Platforms (1st)
 

Mindshare comparison

As of April 2025, in the Streaming Analytics category, the mindshare of Cloudera DataFlow is 0.9%, down from 1.5% compared to the previous year. The mindshare of Databricks is 14.6%, up from 10.1% 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…
ShubhamSharma7 - PeerSpot reviewer
Capability to integrate diverse coding languages in a single notebook greatly enhances workflow
Databricks offers various courses that I can use, whether it's PySpark, Scala, or R. I can leverage all these courses in a single notebook, which is beneficial for clients as they can access various tools in one place whenever needed. This is quite significant. I usually work with PySpark based on client requirements. After coding, I feed the Databricks notebooks into the ADF pipeline for updates. Databricks' capability to process data in parallel enhances data processing speed. Furthermore, I can connect our Databricks notebook directly with Power BI and other visualization tools like Qlik. Once we develop code, it allows us to transform raw data into visualizations for clients using analysis diagrams, which is very helpful.

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."
"DataFlow's performance is okay."
"The initial setup was not so difficult"
"The most effective features are data management and analytics."
"The most valuable feature is the ability to use SQL directly with Databricks."
"Databricks is a scalable solution. It is the largest advantage of the solution."
"I would rate them ten out of ten."
"We have the ability to scale, collaborate and do machine learning."
"Databricks' most valuable feature is the data transformation through PySpark."
"Databricks integrates well with other solutions."
"A very valuable feature is the data processing, and the solution is specifically good at using the Spark ecosystem."
"The technical support is good."
 

Cons

"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 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."
"Cloudera DataFlow's UI interface could be enhanced significantly. Memory handling can also be improved to be better than it is today."
"It's an outdated legacy product that doesn't meet the needs of modern data analysts and scientists."
"Databricks would have more collaborative features than it has. It should have some more customization for the jobs."
"It would be nice to have more guidance on integrations with ETLs and other data quality tools."
"The solution could be improved by integrating it with data packets. Right now, the load tables provide a function, like team collaboration. Still, it's unclear as to if there's a function to create different branches and/or more branches. Our team had used data packets before, however, I feel it's difficult to integrate the current with the previous data packets."
"The integration and query capabilities can be improved."
"The API deployment and model deployment are not easy on the Databricks side."
"The connectivity with various BI tools could be improved, specifically the performance and real time integration."
"Overall it's a good product, however, it doesn't do well against any individual best-of-breed products."
"In the next release, I would like to see more optimization features."
 

Pricing and Cost Advice

"DataFlow isn't expensive, but its value for money isn't great."
"We're charged on what the data throughput is and also what the compute time is."
"Databricks uses a price-per-use model, where you can use as much compute as you need."
"There are different versions."
"The billing of Databricks can be difficult and should improve."
"The price is okay. It's competitive."
"Databricks are not costly when compared with other solutions' prices."
"The licensing costs of Databricks is a tiered licensing regime, so it is flexible."
"The solution is based on a licensing model."
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Top Industries

By visitors reading reviews
University
18%
Computer Software Company
17%
Financial Services Firm
14%
Media Company
6%
Financial Services Firm
17%
Computer Software Company
11%
Manufacturing Company
9%
Healthcare Company
6%
 

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 is your primary use case for Cloudera DataFlow?
We use Cloudera DataFlow for stream analytics.
Which do you prefer - Databricks or Azure Machine Learning Studio?
Databricks gives you the option of working with several different languages, such as SQL, R, Scala, Apache Spark, or Python. It offers many different cluster choices and excellent integration with ...
How would you compare Databricks vs Amazon SageMaker?
We researched AWS SageMaker, but in the end, we chose Databricks. Databricks is a Unified Analytics Platform designed to accelerate innovation projects. It is based on Spark so it is very fast. It...
Which would you choose - Databricks or Azure Stream Analytics?
Databricks is an easy-to-set-up and versatile tool for data management, analysis, and business analytics. For analytics teams that have to interpret data to further the business goals of their orga...
 

Comparisons

 

Also Known As

CDF, Hortonworks DataFlow, HDF
Databricks Unified Analytics, Databricks Unified Analytics Platform, Redash
 

Overview

 

Sample Customers

Clearsense
Elsevier, MyFitnessPal, Sharethrough, Automatic Labs, Celtra, Radius Intelligence, Yesware
Find out what your peers are saying about Cloudera DataFlow vs. Databricks and other solutions. Updated: March 2025.
844,944 professionals have used our research since 2012.