Likelihood to Recommend I find HDP easy to use and solves most of the problems for people looking to manage their big data. Evaluating the Hortonworks Data Platform is easy as it is free to download and install in your cluster. Single node cluster available as Sandbox is also easy for POCs.
Read full review Well suited for my big data related project or a static data set analysis especially for uploading huge dataset to the cluster. But had some issues with connecting IoT real-time data and feeding to Power BI. It might be my understanding please take it as a mere comment rather than a suggestion. Read full review Pros 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. Read full review Jobs with Spark, Hadoop, or Hive queries are rapidly attained Can collect, organize and analyze your data accurately You can customize, for example, Spark or Hadoop configuration settings, or Python, R, Scala, or Java libraries. Read full review Cons 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. Read full review Easier pricing and plug-and-play like you see with AWS and Azure, it would be nice from a budgeting and billing standpoint, as well as better support for the administration. Bundling of the Cloud Object Storage should be included with the Analytics Engine. The inability to add your own Hadoop stack components has made some transfers a little more complex. Read full review Implementation Rating Try not to change variable names.
Read full review Alternatives Considered We chose [Hortonworks Data Platform] because it's free and because [it] was an IBM partner, suggested as big data platform after biginsights platform.
You can install in more physical computer without high specs, then you can use it in order to learn how to deploy, configure a complete big data cluster.
We installed also in a cloud infrastructure of 5 virtual machine
Read full review We initially wanted to go with
Google BigQuery , mainly for the name recognition. However, the pricing and support structure led us to seek alternatives, which pointed us to IBM.
Apache Spark was also in the running, but here IBM's domination in the industry made the choice a no-brainer. As previously stated, the support received was not quite what we expected, but was adequate.
Read full review Return on Investment 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. Read full review This product has allowed us to gather analytics data across multiple platforms so we can view and analyze the data from different workflows, all in one place. IBM Analytics has allowed us to scale on demand which allows us to capture more and more data, thus increasing our ROI. The convenience of the ability to access and administer the product via multiple interfaces has allowed our administrators to ensure that the application is making a positive ROI for our business users and partners. Read full review ScreenShots