Active Query Builder vs. IBM Analytics Engine

This is a good framework to use if your project requires frequent database queries. The product is made for both complete amateurs and seasoned experts. Prompt, courteous, and expert assistance; any problems are addressed and fixed without delay. Relatively inexpensive Inadequate, if there are new people involved, delays due to a lack of documentation are likely, and issues with code completion may arise.

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

• Pull data from SQL even if you do not know SQL.
• Provides clear database information.
• Works with multiple databases at once.
• Data access and security.

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

• Features are good but lacks documentation
• It would be great it were adaptive to Embarcadero/Dev Express Skins that would be very cool
• Modifying SQL code is difficult

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

I have used Flutter to begin and with flutter you need learn a language called Dart which is not needed with AQB, which is the main reason for us to pick Active Query Builder as a choice over Flutter. AQB supports all the merchant SQL databases with native syntax support, query optimizations and more

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

• better business decisions allow us to maximize revenue for the company
• awesome ROI

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