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

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

"The most effective features are data management and analytics."
"This solution is very scalable and robust."
"DataFlow's performance is okay."
"Cloudera DataFlow is fully compatible with Cloudera's ecosystem and offers high efficiency through native connectors for various ecosystems."
"The initial setup was not so difficult"
"The initial setup phase of Databricks was good."
"We can scale the product."
"Databricks is a scalable solution. It is the largest advantage of the solution."
"The processing capacity is tremendous in the database."
"The setup was straightforward."
"Databricks' most valuable features are the workspace and notebooks. Its integration, interface, and documentation are also good."
"The most valuable feature of Databricks is the integration of the data warehouse and data lake, and the development of the lake house. Additionally, it integrates well with Spark for processing data in production."
"The most valuable feature is the ability to use SQL directly with Databricks."
 

Cons

"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."
"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."
"Pricing is one of the things that could be improved."
"I would like to see the integration between Databricks and MLflow improved. It is quite hard to train multiple models in parallel in the distributed fashions. You hit rate limits on the clients very fast."
"The Databricks cluster can be improved."
"The product could be improved by offering an expansion of their visualization capabilities, which currently assists in development in their notebook environment."
"Instead of relying on a massive instance, the solution should offer micro partition levels. They're working on it, however, they need to implement it to help the solution run more effectively."
"The tool should improve its integration with other products."
"CI/CD needs additional leverage and support."
"If I want to create a Databricks account, I need to have a prior cloud account such as an AWS account or an Azure account. Only then can I create a Databricks account on the cloud. However, if they can make it so that I can still try Databricks even if I don't have a cloud account on AWS and Azure, it would be great. That is, it would be nice if it were possible to create a pseudo account and be provided with a free trial. It is very essential to creating a workforce on Databricks. For example, students or corporate staff can then explore and learn Databricks."
 

Pricing and Cost Advice

"DataFlow isn't expensive, but its value for money isn't great."
"The solution is a good value for batch processing and huge workloads."
"The pricing depends on the usage itself."
"I would rate the tool’s pricing an eight out of ten."
"Licensing on site I would counsel against, as on-site hardware issues tend to really delay and slow down delivery."
"We only pay for the Azure compute behind the solution."
"We find Databricks to be very expensive, although this improved when we found out how to shut it down at night."
"I am based in South Africa, where it is expensive adapting to the cloud, and then there is the price for the tool itself."
"I'm not involved in the financing, but I can say that the solution seemed reasonably priced compared to the competitors. Similar products are usually in the same price range. With five being affordable and one being expensive, I would rate Databricks a four out of five."
report
Use our free recommendation engine to learn which Streaming Analytics solutions are best for your needs.
845,040 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
University
18%
Computer Software Company
16%
Financial Services Firm
14%
Media Company
7%
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 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...
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.
845,040 professionals have used our research since 2012.