Modern organizations are harnessing the power of Apache Druid for their AdTech use cases. What will you build?
AdTech and big data are inseparable—to exist in the AdTech industry is to work with terabytes, if not petabytes of data generated from user behavior, ad engagement, real-time auctions, and more. The industry is increasingly reliant on analytics applications as advertisers, ad exchange platforms, and publishers must sift through more data, faster.
Apache Druid was initially designed to power user-facing analytics applications for event-based digital advertising data, ingesting a billion events in under a minute and querying those events in under a second. After a decade of use by over 1,000 organizations, Druid today can manage much larger data sets at even higher speeds.
In this ebook, you’ll get a look at three of the top use cases in AdTech that require real-time ingestion, fast query performance, and high availability. Download your copy to see how companies have leveraged Druid for:
- Real-time Bidding
- Platform and Audience Insights
- Spam and Fraud Detection
What AdTech innovators are saying about Apache Druid
“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.”
Shariq Rizvi, Ads Monetization EVP, Reddit
“By using Druid and Imply for real-time self-service analytics, we can provide our customers with the data they need to improve the performance of their retargeting campaigns.”
Margot Miller, Brand Content Manager, Adikteev