46 Imply Testimonials

“Druid has a distributed architecture, so it's easy for us to scale. As ingestion rates go up, we can add more middle managers and historicals. As more queries come in, we can add more brokers. Finally, Druid has enterprise support from Imply which has helped us tremendously in the past few years.”

“Today we see about 70,000 active users on the platform with about four million queries a day against Apache Druid.”

“A surprising conclusion emerged. The best platform for scalability and customer usage was Imply.”

“After we switched to Druid, our query latencies dropped to near sub-second and in general, the project fulfilled most of our requirements. Today, our cluster ingests nearly 1B+ events per day (2TB of raw data), and Druid has scaled quite well for us.”

“We reduced our infrastructure costs by half and freed up 12 weekly engineering hours, more than covering the cost of Imply.”

“To build our industry-leading solutions, we leverage Imply and Druid, which provide an interactive, highly scalable, and real-time analytics engine, helping us create differentiated offerings.”

“One of the big advantages of Druid has been the customizability that Druid offers; you can pretty much bend it to do anything. ”

“Because Imply has all of these features built-in, engineers focus on making products, not operational work.”

“We built an observability platform powered by Kafka and Druid that ingests over 5 million events per second and handles hundreds of queries on top of that. This gives us real-time insights into the operations of thousands of these Kafka clusters within Confluent Cloud.”

“Druid also has this native Kafka integration out of the box. We don’t even need any sort of connector or anything to make Apache Kafka and Apache Druid work together. It just works.”

“Druid gives us the flexibility to define pre-aggregations, the ability to easily manage ingestion tasks, the ability to query data effectively, and the means to create a highly scalable architecture.”

“Instead of relying on slow and stale dashboards, we have been able to achieve both internal productivity gains and faster decision-making with Druid and Imply.”

“We did a lot of database comparisons, and Druid achieved better query performance. Our team tested Druid and Trino and found Druid was ten times faster on average."

“Combining an approximate streaming algorithm (DataSketch) that supports set operations and a fast time-series datastore (Druid) can provide capabilities that previously could take hours.”

"With Imply, slow queries and syntax struggles have been replaced by slice and dice functionality with sub-second response times. Our team is now armed with a holistic view of both fraud and our application ecosystem."