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

Apache Spark Streaming vs Cloudera DataFlow comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Apache Spark Streaming
Ranking in Streaming Analytics
9th
Average Rating
8.0
Number of Reviews
10
Ranking in other categories
No ranking in other categories
Cloudera DataFlow
Ranking in Streaming Analytics
14th
Average Rating
7.2
Number of Reviews
4
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of November 2024, in the Streaming Analytics category, the mindshare of Apache Spark Streaming is 3.7%, down from 4.7% compared to the previous year. The mindshare of Cloudera DataFlow is 1.4%, down from 1.6% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Streaming Analytics
 

Featured Reviews

Oscar Estorach - PeerSpot reviewer
Jan 25, 2024
Versatile and flexible when dealing with large-scale data streams
What I like about Spark is its versatility in supporting multiple languages and that makes it my preferred choice for building scalable and efficient systems, whether it is hooking databases with web applications or handling large-scale data transformations. Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows. It works well in the cloud, and you can structure data using Databricks or Spark, providing flexibility for different projects. Spark Streaming's flexibility shines when dealing with large-scale data streams. It caters to different needs, offering real-time insights for tasks like online sales analytics. The ability to prioritize data streams is valuable, especially for monitoring competitor prices online.
Júlio César Gomes Fonseca - PeerSpot reviewer
Jun 23, 2023
A stable solution that helps develop quality modules but needs to improve its programming language
Sometimes I need this workflow to make my modules, not for campaign preparation. It is solely focused on developing quality modules for direct telecommunication companies In Cloudera DataFlow, I can't say which is the most valuable feature because we use all modules. We need to compare each…

Quotes from Members

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

Pros

"The solution is very stable and reliable."
"Apache Spark's capabilities for machine learning are quite extensive and can be used in a low-code way."
"Apache Spark Streaming has features like checkpointing and Streaming API that are useful."
"It's the fastest solution on the market with low latency data on data transformations."
"Apache Spark Streaming's most valuable feature is near real-time analytics. The developers can build APIs easily for a code-steaming pipeline. The solutions have an ecosystem of integration with other stock services."
"As an open-source solution, using it is basically free."
"The platform’s most valuable feature for processing real-time data is its ability to handle continuous data streams."
"Apache Spark Streaming was straightforward in terms of maintenance. It was actively developed, and migrating from an older to a newer version was quite simple."
"DataFlow's performance is okay."
"This solution is very scalable and robust."
"The most effective features are data management and analytics."
"The initial setup was not so difficult"
 

Cons

"In terms of improvement, the UI could be better."
"The debugging aspect could use some improvement."
"It was resource-intensive, even for small-scale applications."
"There could be an improvement in the area of the user configuration section, it should be less developer-focused and more business user-focused."
"Integrating event-level streaming capabilities could be beneficial."
"The cost and load-related optimizations are areas where the tool lacks and needs improvement."
"The initial setup is quite complex."
"The solution itself could be easier to use."
"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 and Cost Advice

"I was using the open-source community version, which was self-hosted."
"On a scale from one to ten, where one is expensive, or not cost-effective, and ten is cheap, I rate the price a seven."
"Spark is an affordable solution, especially considering its open-source nature."
"People pay for Apache Spark Streaming as a service."
"DataFlow isn't expensive, but its value for money isn't great."
report
Use our free recommendation engine to learn which Streaming Analytics solutions are best for your needs.
814,649 professionals have used our research since 2012.
 

Top Industries

By visitors reading reviews
Financial Services Firm
23%
Computer Software Company
20%
University
6%
Manufacturing Company
6%
Computer Software Company
19%
Financial Services Firm
16%
University
11%
Manufacturing Company
8%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Apache Spark Streaming?
Apache Spark Streaming is versatile. You can use it for competitive intelligence, gathering data from competitors, or for internal tasks like monitoring workflows.
What needs improvement with Apache Spark Streaming?
The product's event handling capabilities, particularly compared to Kaspersky, need improvement. Integrating event-level streaming capabilities could be beneficial. This aligns with the idea of exp...
What is your primary use case for Apache Spark Streaming?
I've used it more for ETL. It's useful for creating data pipelines, streaming datasets, generating synthetic data, synchronizing data, creating data lakes, and loading and unloading data is fast an...
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.
 

Also Known As

Spark Streaming
CDF, Hortonworks DataFlow, HDF
 

Learn More

 

Overview

 

Sample Customers

UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, eBay Inc.
Clearsense
Find out what your peers are saying about Apache Spark Streaming vs. Cloudera DataFlow and other solutions. Updated: October 2024.
814,649 professionals have used our research since 2012.