Apache Hadoop vs. Red Hat OpenShift

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Hadoop
Score 7.5 out of 10
N/A
Hadoop is an open source software from Apache, supporting distributed processing and data storage. Hadoop is popular for its scalability, reliability, and functionality available across commoditized hardware.N/A
Red Hat OpenShift
Score 9.2 out of 10
N/A
OpenShift is Red Hat's Cloud Computing Platform as a Service (PaaS) offering. OpenShift is an application platform in the cloud where application developers and teams can build, test, deploy, and run their applications.
$0.08
per hour
Pricing
Apache HadoopRed Hat OpenShift
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
HadoopRed Hat OpenShift
Free Trial
NoYes
Free/Freemium Version
YesYes
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Apache HadoopRed Hat OpenShift
Features
Apache HadoopRed Hat OpenShift
Platform-as-a-Service
Comparison of Platform-as-a-Service features of Product A and Product B
Apache Hadoop
-
Ratings
Red Hat OpenShift
8.2
277 Ratings
5% above category average
Ease of building user interfaces00 Ratings8.1239 Ratings
Scalability00 Ratings9.0265 Ratings
Platform management overhead00 Ratings7.9247 Ratings
Workflow engine capability00 Ratings7.9225 Ratings
Platform access control00 Ratings8.5249 Ratings
Services-enabled integration00 Ratings8.2234 Ratings
Development environment creation00 Ratings8.6242 Ratings
Development environment replication00 Ratings8.5229 Ratings
Issue monitoring and notification00 Ratings7.8242 Ratings
Issue recovery00 Ratings7.7240 Ratings
Upgrades and platform fixes00 Ratings8.4243 Ratings
Best Alternatives
Apache HadoopRed Hat OpenShift
Small Businesses

No answers on this topic

AWS Lambda
AWS Lambda
Score 8.3 out of 10
Medium-sized Companies
Cloudera Manager
Cloudera Manager
Score 9.9 out of 10
IBM Cloud Private
IBM Cloud Private
Score 9.6 out of 10
Enterprises
IBM Analytics Engine
IBM Analytics Engine
Score 7.2 out of 10
IBM Cloud Private
IBM Cloud Private
Score 9.6 out of 10
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User Ratings
Apache HadoopRed Hat OpenShift
Likelihood to Recommend
8.0
(37 ratings)
9.1
(266 ratings)
Likelihood to Renew
9.6
(8 ratings)
8.9
(27 ratings)
Usability
8.0
(6 ratings)
8.4
(12 ratings)
Availability
-
(0 ratings)
5.5
(1 ratings)
Performance
8.0
(1 ratings)
8.7
(131 ratings)
Support Rating
7.5
(3 ratings)
6.9
(10 ratings)
In-Person Training
-
(0 ratings)
7.0
(1 ratings)
Online Training
6.1
(2 ratings)
-
(0 ratings)
Implementation Rating
-
(0 ratings)
6.7
(4 ratings)
Contract Terms and Pricing Model
-
(0 ratings)
8.0
(3 ratings)
Professional Services
-
(0 ratings)
7.3
(1 ratings)
Vendor post-sale
-
(0 ratings)
8.0
(1 ratings)
Vendor pre-sale
-
(0 ratings)
8.0
(1 ratings)
User Testimonials
Apache HadoopRed Hat OpenShift
Likelihood to Recommend
Apache
Altogether, I want to say that Apache Hadoop is well-suited to a larger and unstructured data flow like an aggregation of web traffic or even advertising. I think Apache Hadoop is great when you literally have petabytes of data that need to be stored and processed on an ongoing basis. Also, I would recommend that the software should be supplemented with a faster and interactive database for a better querying service. Lastly, it's very cost-effective so it is good to give it a shot before coming to any conclusion.
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Red Hat
Red Hat OpenShift, despite its complexity and overhead, remains the most complete and enterprise-ready Kubernetes platform available. It excels in research projects like ours, where we need robust CI/CD, GPU scheduling, and tight integration with tools like Jupyter, OpenDataHub, and Quiskit. Its security, scalability, and operator ecosystem make it ideal for experimental and production-grade AI workloads. However, for simpler general hosting tasks—such as serving static websites or lightweight backend services—we find traditional VMs, Docker, or LXD more practical and resource-efficient. Red Hat OpenShift shines in complex, container-native workflows, but can be overkill for basic infrastructure needs.
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Pros
Apache
  • Handles large amounts of unstructured data well, for business level purposes
  • Is a good catchall because of this design, i.e. what does not fit into our vertical tables fits here.
  • Decent for large ETL pipelines and logging free-for-alls because of this, also.
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Red Hat
  • We had a few microservices that dealt with notifications and alerts. We used OpenShift to deploy these microservices, which handle and deliver notifications using publish-subscribe models.
  • We had to expose an API to consumers via MTLS, which was implemented using Server secret integration in OpenShift. We were then able to deploy the APIs on OpenShift with API security.
  • We integrated Splunk with OpenShift to view the logs of our applications and gain real-time insights into usage, as well as provide high availability.
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Cons
Apache
  • Less organizational support system. Bugs need to be fixed and outside help take a long time to push updates
  • Not for small data sets
  • Data security needs to be ramped up
  • Failure in NameNode has no replication which takes a lot of time to recover
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Red Hat
  • I wouldn't necessarily say there is look everyday technology transform. I can see a trend wherein Red Hat OpenShift is adopting all the new technology trends and helping their customers align with their priorities and the emerging technology trends. I wouldn't call out various scope for development every day. There is scope for development. It is all how the organizations adopt it and how they deliver it to their customers. I don't want to call out there is scope for development. It's happening. It is a never ending process.
  • At the moment, I don't have anything to call out. We are experiencing Red Hat OpenShift and we can see every day they're coming up with new features as and when they come up with new features, we want to experience it more and more. We are looking for opportunities wherein this can be leveraged to help our users and partners.
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Likelihood to Renew
Apache
Hadoop is organization-independent and can be used for various purposes ranging from archiving to reporting and can make use of economic, commodity hardware. There is also a lot of saving in terms of licensing costs - since most of the Hadoop ecosystem is available as open-source and is free
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Red Hat
OpenShift is really easy of use through its management console. OpenShift gives a very large flexibility through many inbuilt functionalities, all gathered in the same place (it's a very convenient tool to learn DevOps technics hands on) OpenShift is an ideal integrated development / deployment platform for containers
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Usability
Apache
As Hadoop enterprise licensed version is quite fine tuned and easy to use makes it good choice for Hadoop administrators. It’s scalability and integration with Kerberos is good option for authentication and authorisation. installation can be improved. logging can be improved so that it become easier for debugging purposes. parallel processing of data is achieved easily.
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Red Hat
The virtualization part takes some getting used to it you are coming from a more traditional hypervisor. Customization options are not intuitive to these users. The process should be more clear. Perhaps a guide to Openshift Virtualization for users of RHV, VMware, etc. would ease this transition into the new platform
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Reliability and Availability
Apache
No answers on this topic
Red Hat
Redhat openshift is generally reliable and available platform, it ensures high availability for most the situations. in fact the product where we put openshift in a box, we ensure that the availability is also happening at node and network level and also at storage level, so some of the factors that are outside of Openshift realm are also working in HA manner.
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Performance
Apache
No answers on this topic
Red Hat
Overall, this platform is beneficial. The only downsides we have encountered have been with pods that occasionally hang. This results in resources being dedicated to dead or zombie pods. Over time, these wasted resources occasionally cause us issues, and we have had difficulty monitoring these pods. However, this issue does not overshadow the benefits we get from Openshift.
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Support Rating
Apache
It's a great value for what you pay, and most Data Base Administrators (DBAs) can walk in and use it without substantial training. I tend to dabble on the analyst side, so querying the data I need feels like it can take forever, especially on higher traffic days like Monday.
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Red Hat
Every time we need to get support all the Red Hat team move forward looking to solve the problem. Sometimes this was not easy and requires the scalation to product team, and we always get a response. Most of the minor issues were solved with the information from access.redhat.com
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In-Person Training
Apache
No answers on this topic
Red Hat
I was not involved in the in person training, so i
can not answer this question, but the team in my org worked directly
with Openshift and able to get the in person training done easily, i did not
hear problem or complain in this space, so i hope things happen
seamlessly without any issue.
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Online Training
Apache
Hadoop is a complex topic and best suited for classrom training. Online training are a waste of time and money.
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Red Hat
We went thru the training material on RH webesite, i think its very descriptive and the handson lab sesssions are very useful. It would be good to create more short duration videos covering one single aspect of openshift, this wll keep the interest and also it breaks down the complexity to reasonable chunks.
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Implementation Rating
Apache
No answers on this topic
Red Hat
The learning curve is quite high but worth it.
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Alternatives Considered
Apache
Not used any other product than Hadoop and I don't think our company will switch to any other product, as Hadoop is providing excellent results. Our company is growing rapidly, Hadoop helps to keep up our performance and meet customer expectations. We also use HDFS which provides very high bandwidth to support MapReduce workloads.
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Red Hat
The Tanzu Platform seemed overly complicated, and the frequent changes to the portfolio as well as the messaging made us uneasy. We also decided it would not be wise to tie our application platform to a specific infrastructure provider, as Tanzu cannot be deployed on anything other than vSphere. SUSE Rancher seemed good overall, but ultimately felt closer to a DIY approach versus the comprehensive package that Red Hat OpenShift provides.
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Contract Terms and Pricing Model
Apache
No answers on this topic
Red Hat
It's easy to understand what are being billed and what's included in each type of subscription. Same with the support (Std or Premium) you know exactly what to expect when you need to use it. The "core" unit approach on the subscription made really simple to scale and carry the workloads from one site to another.
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Scalability
Apache
No answers on this topic
Red Hat
This is a great platform to deployment container applications designed for multiple use cases. Its reasonably scalable platform, that can host multiple instances of applications, which can seamlessly handle the node and pod failure, if they are configured properly. There should be some scalability best practices guide would be very useful
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Return on Investment
Apache
  • There are many advantages of Hadoop as first it has made the management and processing of extremely colossal data very easy and has simplified the lives of so many people including me.
  • Hadoop is quite interesting due to its new and improved features plus innovative functions.
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Red Hat
  • All of the above. Red Hat OpenShift going into a developer-type setting can be stood up very quickly. There's a very short period to have developers onboard to it and they're able to become productive much faster than a grow your own type solution.
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ScreenShots