Cloudera Distribution for Hadoop and Cloudera Data Platform compete in big data management and analytics. Cloudera Data Platform takes the lead due to its advanced features and scalability.
Features: Cloudera Distribution for Hadoop provides robust data processing capabilities, focuses on Apache Hadoop frameworks, and supports traditional data workloads with HiveQL and Impala for SQL-like query capabilities. Cloudera Data Platform offers advanced features like Kubernetes for container management, better cloud integration, and support for real-time analytics, making it suitable for modern data environments.
Room for Improvement: Cloudera Distribution for Hadoop could enhance ease of deployment, improve integration within the cloud, and expand real-time processing capabilities. Cloudera Data Platform could improve in reducing costs, enhance user interface functionality, and optimize resource management for better efficiency.
Ease of Deployment and Customer Service: Cloudera Distribution for Hadoop typically requires complex setup processes, focusing on on-premises installations needing significant IT resources. Cloudera Data Platform offers simplified deployment models with cloud solutions, enhancing scalability and adaptability. Customer service in Cloudera Data Platform is integrated within the cloud management ecosystem, providing extensive support while Cloudera Distribution may depend more on traditional support channels.
Pricing and ROI: Cloudera Distribution for Hadoop has lower initial costs, offering a decent return on investment for organizations focusing on cost-effectiveness and legacy infrastructure satisfaction. Cloudera Data Platform, while having higher setup costs, provides greater ROI through enhanced functionalities and scalability, delivering long-term benefits in more dynamic data environments.
I have communicated with technical support, and they are responsive and helpful.
The technical support is quite good and better than IBM.
Integration with other tools works well for us and we successfully scaled the solution after two to three years without any issues.
For scalability, I rate Cloudera Data Platform at an eight out of ten as it is an on-premise solution.
We faced challenges but overcame those challenges successfully.
Cloudera Data Platform should include additional capabilities and features similar to those offered by other data management solutions like Azure and Databricks.
We aim to address these issues with a Kubernetes-based platform that will simplify the task of upgrading services.
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.
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 foremost benefit is offloading data from the warehouse to Cloudera Data Platform, which allows for cheaper storage.
It is scalable, ready for vertical scaling, and very powerful, offering numerous functionalities and configurations for generative AI.
Cloudera Data Platform offers a powerful fusion of Hadoop technology and user-centric tools, enabling seamless scalability and open-source flexibility. It supports large-scale data operations with tools like Ranger and Cloudera Data Science Workbench, offering efficient cluster management and containerization capabilities.
Designed to support extensive data needs, Cloudera Data Platform encompasses a comprehensive Hadoop stack, which includes HDFS, Hive, and Spark. Its integration with Ambari provides user-friendliness in management and configuration. Despite its strengths in scalability and security, Cloudera Data Platform requires enhancements in multi-tenant implementation, governance, and UI, while attribute-level encryption and better HDFS namenode support are also needed. Stability, especially regarding the Hue UI, financial costs, and disaster recovery are notable challenges. Additionally, integration with cloud storage and deployment methods could be more intuitive to enhance user experience, along with more effective support and community engagement.
What are the key features?Cloudera Data Platform is implemented extensively across industries like hospitality for data science activities, including managing historical data. Its adaptability extends to operational analytics for sectors like oil & gas, finance, and healthcare, often enhanced by Hortonworks Data Platform for data ingestion and analytics tasks.
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