Cloudera Distribution for Hadoop (CDH) and Cloudera Data Platform (CDP) are major players in managing big data environments, with CDP offering more modern features and flexibility, particularly in security and scalability.
Features: CDP includes enterprise security, efficient cluster management, and easy integration with tools like Ranger, enhancing scalability in hybrid cloud settings. CDH is recognized for its administration via Cloudera Manager, query optimization with Impala, and comprehensive documentation.
Room for Improvement: CDP could benefit from improved Spark and AI workload support, easier integration, and better API documentation. Enhancements in Ranger's security implementation are needed for complex environments. CDH requires better performance in HBase, simpler installation, and improved API customization, while lacking advanced cloud functionality compared to CDP.
Ease of Deployment and Customer Service: CDP supports versatile deployments across on-premises and various cloud configurations, offering better integration and support, whereas CDH focuses on traditional on-premises setups with less flexibility.
Pricing and ROI: CDH's high per-node cost can be challenging at scale, but it offers value in complex setups despite higher initial costs. CDP has a more complex pricing model based on resources like cores and terabytes. Its flexibility in cloud environments can lead to cost efficiency but may also lead to higher costs depending on usage.
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 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.
The technical support is quite good and better than IBM.
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.
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.
We faced challenges but overcame those challenges successfully.
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.
Integrating with Active Directory, managing security, and configuration are the main concerns.
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.
It can be deployed on-premises, unlike competitors' cloud-only solutions.
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.
This is the only solution that is possible to install on-premise.
| Product | Mindshare (%) |
|---|---|
| Cloudera Data Platform | 7.9% |
| Palantir Foundry | 13.5% |
| Informatica Intelligent Data Management Cloud (IDMC) | 10.1% |
| Other | 68.5% |
| Product | Mindshare (%) |
|---|---|
| Cloudera Distribution for Hadoop | 14.7% |
| Apache Spark | 13.9% |
| HPE Data Fabric | 10.2% |
| Other | 61.2% |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 7 |
| Large Enterprise | 26 |
| Company Size | Count |
|---|---|
| Small Business | 16 |
| Midsize Enterprise | 9 |
| Large Enterprise | 32 |
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.
Cloudera Distribution for Hadoop provides a comprehensive platform for efficient data management and analytics, integrating advanced analytics tools with enterprise-grade security and hybrid cloud support.
Designed for handling vast datasets, Cloudera Distribution for Hadoop facilitates seamless data processing through its components such as Hive, Pig, and Spark. It supports both structured and unstructured data management with robust scalability and powerful data handling capabilities. While the latest version focuses on enhancing speed and integration, challenges remain with HBase stability and processing in Cloudera 5 clusters. Organizations leverage it for big data management tasks like data warehousing, log analytics, and real-time data processing using tools like Hadoop and Spark.
What are the key features of Cloudera Distribution for Hadoop?In industries such as finance, retail, and healthcare, Cloudera Distribution for Hadoop is implemented to enhance data-driven decision-making and operational efficiency. It aids in processing large volumes of data for analytics, data warehousing, and infrastructure building. Companies utilize it to streamline machine learning and log analytics, serving as a data lake for preprocessing substantial datasets.
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