Databricks Lakehouse Platform vs Hortonworks Data Platform

• It supports all data science programming languages like Python and R
• it takes very few minutes to deploy models into production
• it has tools that ensures collaborations between developers

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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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• Better Localized Testing
• When they were primarily OSS Spark; it was easier to test/manage releases versus the newer DB Runtime. Wish there was more configuration in Runtime less pick a version.
• Graphing Support went non-existent; when it was one of their compelling general engine.

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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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• Rapid growth of analytics within our company.
• Cost model aligns with usage allowing us to make a reasonable initial investment and scale the cost as we realize the value.
• Platform is easy to learn and Databricks provides excellent support and training.
• Platform does not require a large DevOPs investment

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• It is difficult to have a negative impact, because the required investment is not that high.
• The big open community behind Hortonworks and related Apache Project makes it easy to put 'the wheel to meet the road' quite quickly.
• We have seen management meetings where the attendants were impressed by the results achieved with the datalake built on HDP.

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