Cloudera Manager vs Hortonworks Data Platform

• Graphical user interface
• Management of third party applications start/stop/restart functionality through framework
• Support of Apache Hadoop ecosystem
• Ability to do "rolling restarts"

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• It does a good job of packaging a lot of big data components into bundles and lets you use the ones you are interested in or need. It supports an extensive list of components which lets us solve many problems.
• It provides the ability to manage installations and maintenance using Apache Ambari. It helps us in using management packs to install/upgrade components easily. It also helps us add, remove components, add, remove hosts, perform upgrades in a convenient manner. It also provides alerts and notifications and monitors the environment.
• What they excel in is packaging open source components that are relevant and are useful to solve and complement each other as well as contribute to enhancing those components. They do a great job in the community to keep on top of what would be useful to users, fixing bugs and working with other companies and individuals to make the platform better.

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• Cloudera Manager needs to be more agile with integrating other applications, such as Accumulo 1.7, to their software.
• Cloudera Manager can do a better job at explaining why a node fails to add to a cluster using their assistant.
• Cloudera Manager should show graphs only when there is data, instead of showing just an empty box.

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• Since it doesn't come with propriety tools for big data management, additional integration is need (for query handling, search, etc).
• It was very straightforward to store clinical data without relations, such as data from sensors of a medical device. But it has limitations when needed to combine the data with other clinical data in structured format (e.g. lab results, diagnosis).
• Overall look and feel of front-end management tools (e.g. monitoring) are not good. It is not bad but it doesn't look professional.

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• Cloudera Manager has allowed our organization to deploy Apache Hadoop to operations quicker and with less training versus using the command line exclusively.
• Increased employee efficiency.
• Increased product adoption.

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• Positive ROI for streaming use cases.
• Negative impact on staffing, it will require 1-2 FTEs more than Cloudera or a BI operations team.
• Positive ROI for Ambari and the ELK stack. You will get great capabilities for IT Operations.

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