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.
It provides a positive return on investment for those who can connect multiple data sources and make data-driven decisions easily.
If you don't need to write a whole ETL to make the data virtualization, you need way fewer people to write a query instead of writing an ETL pipeline.
I have seen a return on investment, which showed up in improved customer satisfaction scores.
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.
They have a good methodology for learning how to use the tool.
Denodo's customer support team is very competent and responsive.
If we raise a ticket, it can be resolved or addressed within a reasonable time frame, so support is good.
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.
For huge data requests, it cannot scale automatically; admin action is required.
Denodo's scalability comes into play specifically when there is data transfer.
My client has almost 100 million records, and the performance was impacted in a way that required optimization.
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.
I would rate it nine out of ten because it is very reliable, always performing as expected.
If JVM does not function properly, it may cause Denodo to fail to connect to different sources.
Denodo is stable and good.
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.
Ensuring data caching is up to date is critical.
Denodo needs better communication on how the product can be deployed for specific solutions.
The system has dependencies on other environments, like JVM, which can affect its performance.
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.
For small companies, it's not a solution that most small companies can afford.
Denodo is considered pricey, limiting its use to large enterprises or government organizations that can afford its comprehensive setup.
Denodo's pricing is not affordable for small companies and is more suitable for medium to large enterprises.
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.
Denodo's ability to connect to multiple data sources and perform extract-transform-load (ETL) operations on the fly is noteworthy.
The most valuable feature of Denodo is its uniformity of self-site data access types, which allows it to connect to almost any storage technology and feed it transparently.
Denodo supports SQL base, so if you want to join two tables or two views, you can use SQL, which is an advantage as most developers or business people know SQL.
| Product | Mindshare (%) |
|---|---|
| Cloudera Data Platform | 8.4% |
| Denodo | 4.7% |
| Other | 86.9% |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 7 |
| Large Enterprise | 26 |
| Company Size | Count |
|---|---|
| Small Business | 16 |
| Midsize Enterprise | 6 |
| Large Enterprise | 21 |
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.
Denodo specializes in data virtualization, data cataloging, and user-friendly interfaces. It's recognized for connecting disparate data sources, presenting unified data for analytics, and supporting efficient decision-making with agile analytics and robust data governance.
Denodo effectively aggregates data from multiple sources to offer a comprehensive understanding through its virtualization capabilities. It provides role-based access control, flexible query languages, performance optimization, and integration with databases. Enhancements are needed in its interface and documentation to ensure better user experiences. While the platform supports cloud migration, integration challenges with tools like Salesforce and MuleSoft exist. Improvements in data visualization, automation, and scalability, especially in large data environments, are critical areas for growth.
What are the key features of Denodo?In industries like finance, healthcare, and retail, Denodo plays a crucial role in data virtualization and integration. Organizations use it to unify disparate data systems, enabling real-time analytics and supporting cloud migrations. Denodo's platform is ideal for businesses needing to aggregate, transform, and utilize diverse data efficiently, optimizing operations and enhancing governance.
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