IBM Analytics Engine vs Kibana

• 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.

Kibana integrates seamlessly with Elastic Search which gives us access to parse and analyze data generated from our systems in order to make decisions. Also, Kibana helps us create insightful reports and dashboards that give us insights into the end-users usage on the system and helps us find the root cause of issues as well.

• 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.

• Fast searches with powerful index.
• Beautiful data visualizations.
• Real-time observability.

• 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.

• Some performance issues with large datasets.
• Linking to dashboards makes extremely long urls.
• Lack of reports.

We did not use the official Kibana support. Documentation was easy enough to follow.

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.

Kibana has a better usability experience, the core features I was using existed in all of them. I liked more in Kibana how you can easily create dashboards, charts, and reports without the need to be a tech person.

• 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.

• Improved understanding of production environment.
• Reduced downtime.
• More empowered developers who understand their systems in production.