The Microsoft Azure App Service is a PaaS that enables users to build, deploy, and scale web apps and APIs, a fully managed service with built-in infrastructure maintenance, security patching, and scaling. Includes Azure Web Apps, Azure Mobile Apps, Azure API Apps, allowing developers to use popular frameworks including .NET, .NET Core, Java, Node.js, Python, PHP, and Ruby.
$9.49
per month
Informatica Cloud Data Quality
Score 6.8 out of 10
N/A
The vendor states that Informatica Data Quality empowers companies to take a holistic approach to managing data quality across the entire organization, and that with Informatica Data Quality, users are able to ensure the success of data-driven digital transformation initiatives and projects across users, types, and scale, while also automating mission-critical tasks.
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
Azure App Service
Informatica Cloud Data Quality
Red Hat OpenShift
Editions & Modules
Shared Environment for dev/test
$9.49
per month
Basic Dedicated environment for dev/test
$54.75
per month
Standard Run production workloads
$73
per month
Premium Enhanced performance and scale
$146
per month
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Azure App Service
Informatica Cloud Data Quality
Red Hat OpenShift
Free Trial
Yes
No
Yes
Free/Freemium Version
No
No
Yes
Premium Consulting/Integration Services
No
No
No
Entry-level Setup Fee
No setup fee
No setup fee
No setup fee
Additional Details
Free and Shared (preview) plans are ideal for testing applications in a managed Azure environment. Basic, Standard and Premium plans are for production workloads and run on dedicated Virtual Machine instances. Each instance can support multiple applications and domains.
Redhat has a high license cost but offers support and the ability to run workloads anywhere with practically no changes. Red hat allows easier shelling into a container to inspect what is wrong, VS ECS or EKS. There is a lengthy blog post on how to do that for ECS on AWSs blog. …
You may easily deploy your apps to Azure App Service if they were written in Visual Studio IDE (typically.NET applications). With a few clicks of the mouse, you may already deploy your application to a remote server using the Visual Studio IDE. As a result of the portal's bulk and complexity, I propose Heroku for less-experienced developers.
For effective data collaboration, systematic verification of customer information, and address, among others, Informatica Data Quality is a fruitful application to consider. Besides, Informatica Data Quality controls quality through a cleansing process, giving the company a professional outline of candid data profiling and reputable analytics. Finally, Informatica Data Quality allows the simplistic navigation of content, with a dashboard that supports predictability.
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.
The matching algorithms in IDQ are very powerful if you understand the different types that they offer (e.g., Hamming Distance, Jaro, Bigram, etc..). We had to play around with it to see which best suit our own needs of identifying and eliminating duplicate customers. Setting up the whole process (e.g., creating the KeyGenerator Transformation, setting up the matching threshold, etc..) can be somewhat time consuming and a challenge if you don't first standardize your data.
The integration with PowerCenter is great if you have both. You can either import your mappings directly to PowerCenter or to an XML file. The only downside is that some of the transformations are unique to IDQ, so you are not really able to edit them once in PowerCenter.
The standardizer transformation was key in helping us standardize our customer data (e.g., names, addresses, etc..). It was helpful due to having create a reference table containing the standardized value and the associated unstandardized values. What was great was that if you used Informatica Analyst, a business analyst could login and correct any of the values.
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.
You may wind up putting a lot of eggs in one basket--not necessarily a con but something to keep in mind (most of your data will likely be managed and processed through Microsoft products/services if you fully commit to Azure App Service).
Learning new technology. If you're moving from on-premises to Azure App Service (or any cloud solutions), you'll likely have to rethink how things are done to achieve the same end results (and/or resources may become expensive quickly).
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.
As pointed out earlier, due all the robust features IDQ has, our use f the product is successful and stable. IDQ is being used in multiple sources (from CRM application and in batch mode). As this is an iterative process, we are looking to improve our system efficiency using IDQ.
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
I have given this rating because Azure App Service performs very well in terms of speed, reliability, and reducing overhead, and improves overall team productivity, with a little scope for improvement in complex testing scenarios and configurations, scalability concerns in a large setup, and similar tracking and audit needs.
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
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.
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.
Microsoft has always been known for providing a high standard in terms of customer support and Azure App Service (and as a matter of fact the whole Azure Platform) is no exception. Azure App Service never caused us any issues and we only contacted their customer support for questions regarding server locations and pricing. I feel pretty satisfied with how they treat their customers.
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
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.
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.
When we chose it, we did so because of its integration with Microsoft applications; now we need to integrate with AI, and Azure doesn't offer a good integration. That is the main reason to change it. It is still great to develop Windows- and Microsoft-based applications, but if we need to integrate with AI, Google wins by far.
IDQ is used by a department at my organisation to ensure and enhance the data quality. The usage was started with address standardization and now it had been brought to altogether a next level of quality check where it fixes duplicates, junk characters, standardize the names, streets, product descriptions. In the past we had issues mainly with duplicate customers and products and this were affecting the sales projection and estimates.
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.
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.
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
Deployment of ASP.NET apps at the organization has been sped up.
An option to offer access to the version control system on a third platform so that we could easily deploy our apps.
Because of Azure App Service's scalability capabilities, the costs of running the services are kept to a minimum. As a result, we may save hundreds of dollars each month compared to the expenses of traditional servers by using fewer resources during slack periods.
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.
