StarTree

Fast, Fresh, Actionable Insights at Scale
Real-Time Analytics for Your Business and Your Users. From the Creators of Apache Pinot

Go beyond dashboards and infuse analytics into user-facing apps that provide real-time, actionable insights to your users

Enable your most important stakeholders to make better decisions with the right information, at the right time

Distinguish your products and build new revenue streams while increasing user engagement and loyalty

Proven at scale by millions of LinkedIn members and hundreds of restaurant owners who use UberEats

Within seconds of an event occuring, users get insights that they can act on

That means truly interactive analytics possible at scale

Unify your analytics on one platform that powers multiple use cases including user-facing analytics, anomaly detection, and operational analytics

Ingest data from batch sources like S3, HDFS, ADSL and GCS, as well as streaming sources such as Kafka or Kinesis

Get blazing fast access to both individual events and aggregated data

Today’s innovators are reimagining analytics. Will you be next?

LinkedIn

IGOR PERISIC,CHIEF DATA OFFICER

Apache Pinot revolutionized the way LinkedIn thinks about data analytics and delivers value to our members and customers through highly dimensional, near-real-time insights. Member experiences, such as ‘Who Viewed My Profile’ data, have been enabled at scale thanks to Pinot’s performance profile. As the first company to use this technology, we are thrilled to see StarTree moving quickly toward commercialization so the rest of the world can reap similar benefits from the platform.
Uber

GIRISH BALIGA,ENGINEERING MANAGER

Apache Pinot powers the real-time analytics platform at Uber. It is fast, reliable, scalable, and one of the main engines for our user-facing dashboards and real-time insights.
Stripe

PETER BAKKUM,ENGINEERING MANAGER

Pinot enables us to execute sub-second, petabyte-scale aggregation queries over fresh financial events in our internal ledger. We chose Pinot because of its rich feature set and scalability, which has enabled better performance than our previous solution — at lower cost.