Imply is commonly used for BI use cases. Organizations deploy Imply to accelerate queries and power data applications based on business transaction and interaction data. Unlike many SQL-on-Hadoop engines or data warehouses, Imply is designed for sub-second queries, where users can interactively explore data through a UI.
Imply is a great fit if you are developing a user-facing application and you want your users to be able to not just view a report or static dashboard, but actually get to insights through self-service drill-down, and slice and dice of the data.
Imply was designed to deliver sub-second response to ad hoc queries on massive data sets, without requiring pre-computation. Many customers use Imply to accelerate access to the data in their traditional databases or data lakes.
Benchmarks have found the Apache Druid analytics engine that powers Imply to be 10-100X times faster than Presto or Hive, the most popular SQL-on-Hadoop query engines. While data warehouses are faster than data lakes, they still require 10s of seconds to respond to many queries, which is too slow for reliable interactive use.