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Apache Spark vs Hortonworks Data Platform comparison

 

Comparison Buyer's Guide

Executive Summary
 

Categories and Ranking

Apache Spark
Ranking in Hadoop
1st
Average Rating
8.4
Number of Reviews
64
Ranking in other categories
Compute Service (4th), Java Frameworks (2nd)
Hortonworks Data Platform
Ranking in Hadoop
6th
Average Rating
8.0
Number of Reviews
25
Ranking in other categories
Open Source Databases (15th), Data Management Platforms (DMP) (9th)
 

Featured Reviews

SurjitChoudhury - PeerSpot reviewer
Feb 20, 2024
Offers batch processing of data and in-memory processing in Spark greatly enhances performance
Spark supports real-time data processing through Spark Streaming. It allows for batch processing of data. If you have immediate data, like chat information, that needs to be processed in real-time, Spark Streaming is used. For data that can be evaluated later, batch processing with Apache Spark is suitable. Mostly, batch processing is utilized in our organization, but for streaming data processing, tools like Kafka are often integrated. In-memory processing in Spark greatly enhances performance, making it a hundred times faster than the previous MapReduce methods. This improvement is achieved through optimization techniques like caching, broadcasting, and partitioning, which help in optimizing queries for faster processing.
Leslie Mavonyani - PeerSpot reviewer
Aug 31, 2023
Helps with data management and has good scalability
We use Hortonworks Data Platform for data management, significant data ingestion, and analytics Hortonworks Data Platform has a limited user community. I haven't seen much discussion about user experiences. More information could be there to simplify the process of running the product. We have…

Quotes from Members

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

Pros

"The main feature that we find valuable is that it is very fast."
"One of Apache Spark's most valuable features is that it supports in-memory processing, the execution of jobs compared to traditional tools is very fast."
"The most valuable feature of Apache Spark is its memory processing because it processes data over RAM rather than disk, which is much more efficient and fast."
"Apache Spark can do large volume interactive data analysis."
"I like Apache Spark's flexibility the most. Before, we had one server that would choke up. With the solution, we can easily add more nodes when needed. The machine learning models are also really helpful. We use them to predict energy theft and find infrastructure problems."
"DataFrame: Spark SQL gives the leverage to create applications more easily and with less coding effort."
"AI libraries are the most valuable. They provide extensibility and usability. Spark has a lot of connectors, which is a very important and useful feature for AI. You need to connect a lot of points for AI, and you have to get data from those systems. Connectors are very wide in Spark. With a Spark cluster, you can get fast results, especially for AI."
"The most valuable feature is the Fault Tolerance and easy binding with other processes like Machine Learning, graph analytics."
"The Hortonworks solution is so stable. It is working as a production system, without any error, without any downtime. If I have downtime, it is mostly caused by the hardware of the computers."
"Now, using this solution, it is much cheaper to have all of the data available for searching, not in real-time, but whenever there is a pending request."
"It is a scalable platform."
"The product offers a fairly easy setup process."
"Distributed computing, secure containerization, and governance capabilities are the most valuable features."
"We use it for data science activities."
"The upgrades and patches must come from Hortonworks."
"The scalability is the key reason why we are on this platform."
 

Cons

"The setup I worked on was really complex."
"This solution currently cannot support or distribute neural network related models, or deep learning related algorithms. We would like this functionality to be developed."
"If you have a Spark session in the background, sometimes it's very hard to kill these sessions because of D allocation."
"At times during the deployment process, the tool goes down, making it look less robust. To take care of the issues in the deployment process, users need to do manual interventions occasionally."
"I would like to see integration with data science platforms to optimize the processing capability for these tasks."
"I know there is always discussion about which language to write applications in and some people do love Scala. However, I don't like it."
"Stream processing needs to be developed more in Spark. I have used Flink previously. Flink is better than Spark at stream processing."
"The solution must improve its performance."
"The version control of the software is also an issue."
"The cost of the solution is high and there is room for improvement."
"Since Cloudera acquired HDP, it's been bundled with CBH and HDP. However, the biggest challenge is cloud storage integration with Azure, GCP, and AWS."
"It's at end of life and no longer will there be improvements."
"Security and workload management need improvement."
"It would also be nice if there were less coding involved."
"I work a lot with banking, IT and communications customers. Hortonworks must improve or must upgrade their services for these sectors."
"More information could be there to simplify the process of running the product."
 

Pricing and Cost Advice

"Considering the product version used in my company, I feel that the tool is not costly since the product is available for free."
"Apache Spark is an open-source solution, and there is no cost involved in deploying the solution on-premises."
"They provide an open-source license for the on-premise version."
"The solution is affordable and there are no additional licensing costs."
"We are using the free version of the solution."
"Since we are using the Apache Spark version, not the data bricks version, it is an Apache license version, the support and resolution of the bug are actually late or delayed. The Apache license is free."
"Spark is an open-source solution, so there are no licensing costs."
"Apache Spark is an expensive solution."
"It is priced well and it is affordable"
"Currently, we are using the product in a sandbox environment, and there is no licensing. We might choose a licensing option once we get the results."
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Top Industries

By visitors reading reviews
Financial Services Firm
26%
Computer Software Company
13%
Manufacturing Company
8%
Educational Organization
5%
Computer Software Company
21%
Financial Services Firm
14%
Government
10%
University
9%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
 

Questions from the Community

What do you like most about Apache Spark?
We use Spark to process data from different data sources.
What is your experience regarding pricing and costs for Apache Spark?
Compared to other solutions like Doc DB, Spark is more costly due to the need for extensive infrastructure. It requires significant investment in infrastructure, which can be expensive. While cloud...
What needs improvement with Apache Spark?
The main concern is the overhead of Java when distributed processing is not necessary. In such cases, operations can often be done on one node, making Spark's distributed mode unnecessary. Conseque...
What do you like most about Hortonworks Data Platform?
Distributed computing, secure containerization, and governance capabilities are the most valuable features.
What is your experience regarding pricing and costs for Hortonworks Data Platform?
I haven't done a price analysis specifically for HDP. However, when it was first introduced as Hadoop 2.0, there were a few use cases where the price was quite high. It was particularly expensive f...
What needs improvement with Hortonworks Data Platform?
Since Cloudera acquired HDP, it's been bundled with CBH and HDP. However, the biggest challenge is cloud storage integration with Azure, GCP, and AWS. These platforms offer competitive storage solu...
 

Also Known As

No data available
Hortonworks, HDP
 

Learn More

 

Overview

 

Sample Customers

NASA JPL, UC Berkeley AMPLab, Amazon, eBay, Yahoo!, UC Santa Cruz, TripAdvisor, Taboola, Agile Lab, Art.com, Baidu, Alibaba Taobao, EURECOM, Hitachi Solutions
Mayo Clinic, Symantec, Progressive Insurance, Noble Energy, Cardinal Health, Rogers, Mercy, Neustar, TRUECar, T-Mobile
Find out what your peers are saying about Apache Spark vs. Hortonworks Data Platform and other solutions. Updated: October 2024.
814,649 professionals have used our research since 2012.