Compare Hortonworks Data Platform vs. Spark SQL

Cancel
You must select at least 2 products to compare!
Quotes From Members

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

Pros
"The scalability is the key reason why we are on this platform.""Hortonworks should not be expensive at all to those looking into using it.""The data platform is pretty neat. The workflow is also really good."

More Hortonworks Data Platform Pros »

"Overall the solution is excellent.""The speed of getting data.""The performance is one of the most important features. It has an API to process the data in a functional manner.""It is a stable solution.""Data validation and ease of use are the most valuable features."

More Spark SQL Pros »

Cons
"The version control of the software is also an issue.""It would also be nice if there were less coding involved."

More Hortonworks Data Platform Cons »

"The solution needs to include graphing capabilities. Including financial charts would help improve everything overall.""Anything to improve the GUI would be helpful.""In the next update, we'd like to see better performance for small points of data. It is possible but there are better tools that are faster and cheaper.""Being a new user, I am not able to find out how to partition it correctly. I probably need more information or knowledge. In other database solutions, you can easily optimize all partitions. I haven't found a quicker way to do that in Spark SQL. It would be good if you don't need a partition here, and the system automatically partitions in the best way. They can also provide more educational resources for new users.""There should be better integration with other solutions."

More Spark SQL Cons »

Pricing and Cost Advice
"It is priced well and it is affordable"

More Hortonworks Data Platform Pricing and Cost Advice »

"The solution is open-sourced and free."

More Spark SQL Pricing and Cost Advice »

report
Use our free recommendation engine to learn which Hadoop solutions are best for your needs.
534,299 professionals have used our research since 2012.
Questions from the Community
Top Answer: The data platform is pretty neat. The workflow is also really good.
Top Answer: I think it is priced well and it is affordable. Hadoop, which we use with the solution, is open-source. That part is free. We pay only for whatever wrappers Cloudera provides on top of the open-source… more »
Top Answer: The NiFi platform could be enhanced. This refers to the data ingestion in a workflow. It would also be nice if there was less coding involved.
Top Answer: It is a stable solution.
Top Answer: Being a new user, I am not able to find out how to partition it correctly. I probably need more information or knowledge. In other database solutions, you can easily optimize all partitions. I haven't… more »
Top Answer: We use it to gather all the transaction data. We have Hadoop and Spark in our system, and we use some easy process flows for transport.
Ranking
5th
out of 22 in Hadoop
Views
1,704
Comparisons
1,135
Reviews
2
Average Words per Review
348
Rating
8.5
4th
out of 22 in Hadoop
Views
662
Comparisons
286
Reviews
5
Average Words per Review
297
Rating
7.0
Comparisons
Also Known As
Hortonworks, HDP
Learn More
Overview
Hortonworks is a leading innovator in the industry, creating, distributing and supporting enterprise-ready open data platforms and modern data applications. Our mission is to manage the world's data. We have a single-minded focus on driving innovation in open source communities such as Apache Hadoop, NiFi, and Spark. We along with our 1600+ partners provide the expertise, training and services that allow our customers to unlock transformational value for their organizations across any line of business. Our connected data platforms powers modern data applications that deliver actionable intelligence from all data: data-in-motion and data-at-rest. We are Powering the Future of Data.
Spark SQL is a Spark module for structured data processing. Unlike the basic Spark RDD API, the interfaces provided by Spark SQL provide Spark with more information about the structure of both the data and the computation being performed. There are several ways to interact with Spark SQL including SQL and the Dataset API. When computing a result the same execution engine is used, independent of which API/language you are using to express the computation. This unification means that developers can easily switch back and forth between different APIs based on which provides the most natural way to express a given transformation.
Offer
Learn more about Hortonworks Data Platform
Learn more about Spark SQL
Sample Customers
Mayo Clinic, Symantec, Progressive Insurance, Noble Energy, Cardinal Health, Rogers, Mercy, Neustar, TRUECar, T-Mobile
UC Berkeley AMPLab, Amazon, Alibaba Taobao, Kenshoo, Hitachi Solutions
Top Industries
VISITORS READING REVIEWS
Computer Software Company34%
Comms Service Provider17%
Media Company10%
Financial Services Firm7%
VISITORS READING REVIEWS
Computer Software Company32%
Comms Service Provider26%
Financial Services Firm8%
Healthcare Company6%
Company Size
REVIEWERS
Small Business30%
Midsize Enterprise17%
Large Enterprise52%
No Data Available
Find out what your peers are saying about Hortonworks Data Platform vs. Spark SQL and other solutions. Updated: September 2021.
534,299 professionals have used our research since 2012.

Hortonworks Data Platform is ranked 5th in Hadoop with 2 reviews while Spark SQL is ranked 4th in Hadoop with 5 reviews. Hortonworks Data Platform is rated 8.6, while Spark SQL is rated 7.0. The top reviewer of Hortonworks Data Platform writes "A modeling and analysis data platform that is inexpensive and stable". On the other hand, the top reviewer of Spark SQL writes "GUI could be improved. Useful for speedily processing big data". Hortonworks Data Platform is most compared with HPE Ezmeral Data Fabric, Amazon EMR, Cloudera DataFlow, Apache Spark and Cloudera Distribution for Hadoop, whereas Spark SQL is most compared with IBM Db2 Big SQL, Amazon EMR, Apache Spark, Informatica Big Data Parser and Netezza Analytics. See our Hortonworks Data Platform vs. Spark SQL report.

See our list of best Hadoop vendors.

We monitor all Hadoop reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.