46 Imply Testimonials

“Our advertisers were requesting different slices of their data and [HBase] didn't really support that. We said what’s next for us? And we chose Apache Druid because it met all our key requirements.”

“We use to wait for a day or two to crunch the data for A/B testing, for example. Now, we can get that data from Druid in real time, usually in less than two seconds.”

“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.”

“Our customers gain insights about their grid and at the same time the platform recommends different products for them to offer their customers, based on the insights we see.”

“One of the reasons we chose Druid is for the active community—it’s open and transparent, and people can review and contribute to the technology."

“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.”

“The sheer volume of data we push through Imply is immense, but in an instant, we can answer a precise question like ‘How many ad opportunities were there for Words with Friends in Brighton today at 4 PM?’”

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

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

“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.”

“The team at Imply are Druid experts and provide best practices on Druid and Imply cluster design. We have also partnered with Imply to deliver additional Pivot UI functionality including alerting users when data hits designated thresholds, email reporting, and UX improvements around slicing and dicing data.”

“The feature that we immediately loved is the Cluster Manager. With it, we can start a new Druid cluster in our AWS VPC or launch a major update in one click. Before, it was a time-consuming and dreaded operation for our data team.”

"Imply’s Pivot enables users across NTT GIN to freely explore data. Users have unlocked new use cases, are creating their own customized dashboards, and are freely sharing insights."

“We built an anomaly detection engine, which uses ML models to detect unusual activity. Druid helps us analyze data with an interactive experience that enables on-demand analysis and visualization.”

“By using Apache Druid and Imply, we can ingest multiple events straight from Kafka and our data lake, ensuring advertisers have the information they need for successful campaigns in real time.”