Imply's new podcast, "Tales at Scale," delves into the world of real-time analytics, featuring stories from developers and engineers, with a focus on Apache Druid. Apache Druid's origin story is recounted by co-creator Eric "Cheddar" Tschetter, who describes the initial challenges faced by a data team in 2011 requiring rapid aggregation of real-time data for digital ad auctions, leading to the creation of a new database. Despite existing solutions such as relational databases, Hadoop, and HBase, the need for handling multiple data dimensions efficiently sparked the development of Druid, which was built to support transparency and visibility needs in ad marketplaces. Over time, Druid expanded its capabilities, notably through the use of sketches for data approximations, and embraced open-source development to refine its features and enhance scalability. Today, Druid supports SQL query integration, has applications across various domains like telecommunications, and continues to evolve in the crowded real-time analytics space, positioning itself as a top choice for building analytics applications.