Hortonworks Data Platform vs. IBM Analytics Engine vs. OpenText Magellan

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.

Incentivized

• 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.

Incentivized

If you do not have a large budget and are a large organization, I would steer clear of Actuate. If you are looking to do very complex washboarding, I would not use them. Your developers have to be very skilled to work with this. Plan to bring in consultants if necessary to help your process. Adhoc reporting is weak. If your pricing is user based and you expand, this could be very expensive.

• 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.

Incentivized

• 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.

Incentivized

• The report outputs can vary across different types such as HTML, PDF, and Excel
• Their open source offering is very sufficient
• There are great boards and blogs for developers and engineers to expand and use their features.
• The people from the company that I've worked with are professional and courteous.

Incentivized

• 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.

Incentivized

• 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.

Incentivized

• The documentation on all the available features, but most importantly on the scripting side, can be improved
• The standard look & feel of some basic options, like parameter selection or sorting and filtering, looks dated and can't be customized
• The server portal needs to provide better tools
• More integration is needed with other OpenText products

Incentivized

I am no longer working for the company that was using Actuate but I believe they would continue to use it because the stitching costs would be to high. It would require a complete rewrite of the reports and the never version of Actuate (BIRT) even required an almost complete report rewrite

Incentivized

It is quite intuitive to use. It is fit specifically for doing sentiment, emotion, and intention analysis as well as text classification and text summarization. I would have given 10 if it is fit for the purpose of doing image processing and analysis as well. There is a huge market to analyze video and image data.

Incentivized

Always there on the front and backend for us and the client.

Try not to change variable names.

Incentivized

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

Incentivized

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.

Incentivized

It is vastly superior to these in many ways, for complex reporting it is a much more sophisticated solution. Visualizations are very good. Javascript extensibility is very powerful, others don't support this or as well. Pentaho and MS are both OLAP oriented. Pentaho is moving more toward big data, which was not our primary focus. Others are stuck in the Crystal Reports Band metaphor.

• 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.

Incentivized

• 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.

Incentivized

• Actuate can handle 50 to 60 sub reports inside a report very well.
• Dynamically creating the datasource, chart, graph, reports are the main advantages. We can do any level of drilling, and can create a performance matrix dashboard efficiently.