Real-Time Analytics with Apache Pinot | Stripe | DoorDash

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We welcome you to join us for an in-person meetup hosted by the Apache Pinot community at DoorDash!
Join us to learn how companies like Stripe and DoorDash use Real-Time Analytics with Apache Pinot and deep dive into their use cases.

Agenda:
5:00-5:30 Snacks and Networking
05:30-05:35- Opening remarks
05:35-05:55 Intro to Real-Time Analytics with Pinot | Tim Berglund, VP of DevRel @ StarTree
05:55-06:15 Building a real-time analytics platform | Lakshmi Rao, Staff Engineer @ Stripe
06:15-06:35 Supporting Multiple Pinot Use Cases at Scale | Will Gan, Software Engineer @ DoorDash
06:35-07:30- Networking and snacks

For more info, please contact community@startree.ai
or reach out on Slack
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Intro to Real-Time Analytics with Pinot | Tim Berglund, VP of DevRel @ StarTree
Analytics is arguably the oldest task of digital computers, and has remained an important part of business computing during its 80-year history. What could possibly be new in this space? A better way to serialize data? A better way to run distributed queries over a data lake? An exciting new integration technology? We need all these things urgently, but to be ready for the future, we something even more: we need analytics that can deliver results to users in real time, in the interaction layer, not to internal decision makers seconds or minutes later. We need what Apache Pinot delivers.
Pinot is a database optimized to serve analytical queries at extremely high levels of concurrency, at latencies measured in the tens of milliseconds, on data ingested from the streaming pipeline that underlies more and more of the systems we're building. It's an OLAP database, but one engineered from the ground up to power user-facing features, not executive-facing dashboards. In this talk, we'll look at how it's built, how to get data into it, how to query it, and the typical role it plays in a next-generation system exposing analytics-powered features to its users.

Building a real-time analytics platform | Lakshmi Rao, Staff Engineer @ Stripe
The stream analytics team has been running Apache Pinot in production for ~ 2 years powering merchant-facing real-time dashboards, real-time fraud and risk analytics, internal financial data dashboards amongst other use cases. These use cases demand sub-second latencies, have a high emphasis on fidelity and require freshness to be in the order of seconds. This talk will give an overview of Pinot's architecture, deployment model and user experience @ Stripe. The talk will also dive deeper into some of the challenges and the lessons that were learnt along the way and set the stage for the next-gen Pinot platform we're building.

Supporting Multiple Pinot Use Cases at Scale | Will Gan, Software Engineer @ DoorDash
At DoorDash, we use Pinot for a few customer-facing analytics use cases and some internal analytics / dashboarding use cases. In this presentation, we cover how we’ve been able to support both, from our deployment setup to our custom pipelines to our use of new features like Tiered Storage.