There are numerous companies of various sizes in production with Druid. This list is incomplete and we hope to add everyone's use cases in the near future.
Druid is used to power dynamic analytics and charting in Archive-It Reports. Reports help Archive-It partners understand what content they captured, why some content did not get captured, and assists with quality assurance and crawl scoping to ensure they are building the highest quality collections.
DripStat uses Druid as a timeseries database to power the DripStat GUI. DripStat ingests transactional data for Java, Scala, and Groovy applications into Druid.
eBay uses Druid to aggregate multiple data streams for real-time user behavior analytics by ingesting up at a very high rate(over 100,000 events/sec), with the ability to query or aggregate data by any random combination of dimensions, and support over 100 concurrent queries without impacting ingest rate and query latencies.
Jolata leverages Druid as the analytics data store for the realtime network perfomance managment platform. Injesting over 35 billion events per day, Jolata calculates a billion metrics every minute to visualize precise network metrics in real-time, and enable operators to quickly drill down and perform root cause analysis.
LDMobile is a mobile DSP for the RTB. We use Druid to aggregate some metrics in order to propose to our customers a real-time dashboard showing performance indicators of their campaigns.
LiquidM uses Druid for real-time drill-down reporting. LiquidM is also contributing back to the community by creating and maintaining a ruby client library for interacting with Druid located at http://github.com/liquidm/ruby-druid.
Druid is the primary data store for Metamarkets’ full stack visual analytics service for the RTB (real time bidding) space. Ingesting over 30 billion events per day, Metamarkets is able to provide insight to its customers using complex ad-hoc queries at a 95th percentile query time of around 1 second.
N3TWORK uses Druid for real-time analysis of its Internet of Interests social entertainment network. It uses Druid analytics both to optimize user experiences and to guide the evolution of its product.
Netflix engineers use Druid to aggregate multiple data streams, ingesting up to two terabytes per hour, with the ability to query data as its being ingested. They use Druid to pinpoint anomalies within their infrastructure, endpoint activity and content flow.
The Druid production deployment at PayPal processes a very large volume of data and is used for internal exploratory analytics by business analytic teams. Here is what they have to say:
Around early Feb, 2014, the Paypal Tracking Platform team, lead by Suresh Kumar, stumbled upon an article talking about a new upcoming kid in Real Time Analytics world. After first glance it seemed just like any other new cool looking technology. But after reading little deeper into the papers(they had referred) and few blogs, it was clear it is different. The fundamental approach to query the data itself looked very different and refreshing.
Coincidently, at the same time, the team was struggling to create a very high volume real-time data query system. We had already explored Drill, Hive, Cassandra, TSDB, Shark etc. Dating back at least a year, none of these technologies were fulfilling our low latency needs for very high volumes of data.
So, as an option we started the Druid prototype and within couple of weeks it was looking like a very promising alternate. Very soon with great help from Core Druid development team our prototype was doing great.
We then started the prototype with large 7-10 billion records and see the response time for query. It was quite amazing.
Today our Druid implementation in PayPal processes a very large volume of Data and is used for our internal exploratory analytics by business analytic teams.
The thing we liked the most was amazing support provided by core Druid team. I have never seen a Open Source Community providing such a very high level of responsiveness for ANY issue related to Druid setup and tuning.
Streamlyzer uses Druid as a next generation online video analytics for online video companies or publishers. Streamlyzer is gathering information from real end-users of our customers and provides visualized real-time analytics in dashboard showing how video contents are delivered and how end-users are experiencing the streaming service.
TWC uses Druid for exploratory analytics.
ViralGains uses Druid for real-time analysis of millions of viral video views, shares, and conversations.
Yahoo uses Druid to power various customer-facing audience and advertising analytics products.
YeahMobi uses Druid to power a dashboard used for ad-tech analytics such as impression and conversion tracking, unique IP statistics, and aggregating metrics such as costs and revenues.