

Find out in this report how the two Data Management Platforms (DMP) solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
There are licensing costs that have been saved when we moved some of the data platforms, decommissioned them, and moved on to this platform.
In terms of return on investment, I see great changes in operational effectiveness measured by RTO when comparing on-premises solutions with cloud solutions.
A specific example of the positive impact of Cloudera Data Platform is the clearly saved time and improved performance, which is the main result of it.
I have seen a return on investment with SAS Viya Platform in the form of money saved, as this is scalable and on the cloud, whereas previously we had to pay for space and on-premises servers.
We generate revenue from the data visualization options, which is a very important key aspect for return of investment.
The relevant metrics definitely show time saved because it is able to crunch 50 to 60,000 rows of numbers in a matter of five to ten minutes, which is a huge improvement.
I would rate the customer support of Cloudera Data Platform ten out of ten.
I have communicated with technical support, and they are responsive and helpful.
Cloudera support is timely and responsive, adhering to the SLAs they provide.
I would rate customer support for SAS Viya Platform a 10 out of 10.
we have received help whenever we have asked, and their response time is quite fast
we got the solution on time
CDP allows for easy, mostly automated scalability where I can schedule job workflows, fine-tune system resource metrics, and add nodes with just a click.
They have the cloud burst feature available where if the on-premises capacity is not sufficient at a point in time, you can run that Spark job on the cloud itself.
The ability to scale processing capacity on demand for batch jobs without impacting other workloads, and support for a growing number of concurrent users and teams accessing the platform simultaneously are significant advantages.
We have not had a problem, and it is because it is on the cloud, it scales quite well.
SAS Viya Platform is quite scalable and can handle large data volumes.
SAS Viya Platform's scalability is great; it can be scaled throughout the project, even company-wide.
Sometimes the end user is not experienced or does not have all the expertise related to Cloudera specifically, making it very difficult to manage properly
Sometimes a node goes down, but it automatically returns to a healthy state.
Cloudera Data Platform is pretty stable in my experience; there are not any downtime or reliability issues.
SAS Viya Platform is good, scalable, and stable.
In my experience, SAS Viya Platform is stable and perfect.
SAS Viya Platform's output has been very robust and accurate.
We aim to address these issues with a Kubernetes-based platform that will simplify the task of upgrading services.
Cloudera Data Platform should include additional capabilities and features similar to those offered by other data management solutions like Azure and Databricks.
Cloudera Data Platform can be improved by addressing the feasibility of using it in the cloud; there are some complexities around the components used in cloud by Cloudera Data Platform that are not really convenient.
Two main improvements would transform this into a great tool: improving the UI and calculation capabilities, and merging AI capabilities.
The cost is also quite high; SAS Viya Platform via SaaS can be expensive compared to some open-source or other cloud alternatives.
In comparison, other packages I have used are more complete and less divided; SAS is quite divided, particularly with quality control, which used to be included, but now requires separate packages for control charts and so on.
Initially, CDH had a straightforward pricing model based on nodes, but CDP includes factors like processors, cores, terabytes, and drives, making it difficult to calculate costs.
We find Cloudera Data Platform to be cost-effective.
So far, I would say that it is competitive pricing that we have received.
I did check with Reddit and they indicated that SAS Viya Platform is a pretty expensive program.
My experience with pricing, setup cost, and licensing is very positive, as the pricing is good and efficient for my organization.
My experience with pricing, setup cost, and licensing for SAS Viya Platform was smooth.
By using the Hadoop File System for distributed storage, we have 1.5 petabytes of physical storage with 500 terabytes of effective storage due to a replication factor of three.
The Ranger integration makes it more flexible and reliable for me by allowing control over data access, specifying who can access at what level, such as table level, masking, or data layer level.
What stands out the most in Cloudera Manager are SDX, which provide centralized control for governance, security, and data lineage across multiple sources.
SAS Viya Platform has improved the speed, scalability, and accessibility of data, leading to more efficient and informed decision-making.
SAS Viya Platform has positively impacted my organization by saving time compared to when we were using SAS 9.4.
The speed and documentation of SAS Viya Platform helped me in my coursework because we were having very intense analyses done and we needed to submit a lot of assignments and analyses as quickly as possible.
| Product | Mindshare (%) |
|---|---|
| Cloudera Data Platform | 7.3% |
| SAS Viya Platform | 4.3% |
| Other | 88.4% |

| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 7 |
| Large Enterprise | 26 |
| Company Size | Count |
|---|---|
| Small Business | 2 |
| Midsize Enterprise | 10 |
| Large Enterprise | 7 |
Cloudera Data Platform provides efficient data management through features like Hue, Spark, and Impala. It integrates open-source solutions, supports hybrid environments, and enhances data governance while prioritizing security, scalability, and cost-effectiveness.
Cloudera Data Platform addresses data management needs by supporting large-scale analytics, data science, and ETL processes. It facilitates seamless operation with Ambari UI for deployment and monitoring. Users benefit from robust security via Ranger, open-source compatibility, and a flexible eco-system that uses Hadoop components. While it simplifies setup and supports hybrid workloads, improvements in AI, machine learning, stability in Name Node High Availability, and cost management are ongoing needs. Challenges in tool usability, governance maturity, and scalability call for continued innovation, especially in cloud adoption and staying aligned with open-source technologies.
What are the key features of Cloudera Data Platform?Organizations in banking, healthcare, and hospitality leverage Cloudera Data Platform for data management, analytics, and cross-source integration. It handles complex data structures, bolsters AI workloads, and adheres to data compliance standards while integrating with tools like Spark, Kafka, and machine learning models.
SAS Viya Platform is an advanced data management and analytics tool designed to deliver powerful insights and foster collaboration across teams. It provides flexible and scalable solutions for data analysis, perfect for tech-savvy professionals seeking robust analytics capabilities.
SAS Viya Platform enhances data-driven decisions with its cloud-enabled analytics capabilities. By supporting open-source integration and visual data manipulation, it caters to a diverse range of analytical needs. Its innovative approach to machine learning and AI streamlines operations, helping companies achieve efficient data utilization strategies across departments. Offering robust technical support, it facilitates seamless implementation and rapid adoption, making it ideal for informed analytics exploration.
What are the key features of SAS Viya Platform?SAS Viya Platform is widely adopted across industries like banking, healthcare, and retail, offering tailored analytics solutions to address industry-specific challenges. In healthcare, for instance, it streamlines patient data insights, while in banking, it optimizes fraud detection processes. In retail, it enhances customer experience analytics, demonstrating its versatile application.
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