![[Distributed Tracing NYC] Distributed Transactions Parallel Commits @UberEngineering](https://i.ytimg.com/vi/Ize6coEqF98/maxresdefault.jpg)
Uploaded December 2019 | Updated September 2026, 2 weeks ago
During a September 2019 meetup hosted at Uber's NYC Engineering Office, Peter Mattis, co-founder of Cockroach Labs, discusses how distributed transactions work and explains the benefits of parallel commits through foundational computer science theory.
During a September 2019 meetup hosted at Uber's NYC Engineering Office, Peter Mattis, co-founder of Cockroach Labs, discusses how distributed transactions work and explains the benefits of parallel commits through foundational computer science theory.
![[Distributed Tracing NYC] Distributed Transactions Parallel Commits](https://i.ytimg.com/vi/Ize6coEqF98/mqdefault.jpg "[Distributed Tracing NYC] Distributed Transactions Parallel Commits
During a September 2019 meetup hosted at Ubers NYC Engineering Office, Peter Mattis, co-founder of Cockroach Labs, discusses how distributed transactions work and explains the benefits of parallel commits through foundational computer science theory.")
![[Visualization Nights] SharedStreets.io](https://i.ytimg.com/vi/J5FxlVnI2DE/mqdefault.jpg "[Visualization Nights] SharedStreets.io
During Ubers September 2019 Visualization Nights meetup, SharedStreet engineer Morgan Herlocker introduces SharedStreets and discusses how their open source software enables public-private collaboration around and the exchange of transportation data. In this talk, he also demonstrates how to link Uber Movement data with OpenStreetMap and load the data set for visualization in Kepler.gl")
![[Uber Open Source] Petastorm: Uber ATGs Data Access Library for Deep Learning Yevgeni Litvin](https://i.ytimg.com/vi/J5SILwWOktM/mqdefault.jpg "[Uber Open Source] Petastorm: Uber ATGs Data Access Library for Deep Learning Yevgeni Litvin
During a March 2019 meetup hosted at Ubers SF office, Uber ATG staff software engineer Yevgeni Litvin discusses how data produced and managed by Big Data systems like Apache Spark and Apache Hive cannot be directly consumed by Deep Learning systems like TensorFlow and PyTorch.")
![[Destination:Web] JavaScript Errors Demystified](https://i.ytimg.com/vi/KpeftlLF99c/mqdefault.jpg "[Destination:Web] JavaScript Errors Demystified
During a May 2019 meetup hosted at Uber’s San Francisco office, Sentry engineer, Ben Vinegar discusses Collecting JavaScript errors from the browser: its harder than you think. Join him down the rabbit hole of normalizing stack traces, managing CORS, and unwrangling uncaught promise errors.")
![[Uber Mobility] Memory Leak Hunt: LeakCanary - Pierre-Yves Ricau](https://i.ytimg.com/vi/KwArTJHLq5g/mqdefault.jpg "[Uber Mobility] Memory Leak Hunt: LeakCanary - Pierre-Yves Ricau
During our May 30, 2018 Uber Mobility meetup, Square engineer Pierre-Yves Ricau walks through the mental process involved in understanding a leak trace with a live app demo.")
![[Uber Open Summit 2018] Large-Scale Geospatial Visualization in the Browser with deck.gl](https://i.ytimg.com/vi/L2ShgAe85Fg/mqdefault.jpg "[Uber Open Summit 2018] Large-Scale Geospatial Visualization in the Browser with deck.gl
Visualization and interaction with large-scale geospatial datasets is crucial to understanding the pulsing lives and transportation in our cities. deck.gl is a WebGL-powered data visualization framework and the foundation to many real-time, high-performance web applications that power Uber’s business and beyond. During this hands-on workshop, engineer Xiaoji Chen teaches Uber Open Summit 2018 attendees about deck.gl’s core concepts and capabilities via real-world examples.")
![[Destination:Web] Accessibility for Modern Web Apps](https://i.ytimg.com/vi/LCtaccHLjUA/mqdefault.jpg "[Destination:Web] Accessibility for Modern Web Apps
Asynchronous iterators combine the async and await keywords with generator functions, providing an elegant way to express streaming operations in modern JavaScript applications. In this Destination:Web talk, Stripes Paul Ryan explores a real-world use case for async iterators and demonstrates how to properly use the feature with cancellation.")
![[Uber Seattle] Building Reliable Microservices @ Uber Siva Kalva](https://i.ytimg.com/vi/LFyK-Li2-ZQ/mqdefault.jpg "[Uber Seattle] Building Reliable Microservices @ Uber Siva Kalva
During a June 2018 meetup, engineering manager Siva Kalva discusses how we designed both the reliability tool chain our developers use when building microservices as well as their flow when deploying changes to production.")
![[Uber Open Source] New Features in Pinot: Standard SQL and Cloud Readiness](https://i.ytimg.com/vi/LayrViOqiOM/mqdefault.jpg "[Uber Open Source] New Features in Pinot: Standard SQL and Cloud Readiness
Apache Pinot is a distributed columnar database for real-time analytics. It powers many well-known applications, including LinkedIn’s Who Viewed My Profile feature and Uber Eats timely analytics. Since Pinot joined Apache Incubator in 2019, it has gained a lot of momentum with a growing community.
During this May 2020 Uber Engineering Meetup, software engineers Sidd and Xiang introduces new Apache Pinot integrations and features, including ORDER BY, DISTINCT, Text Search, and Standard SQL. They also discuss work being done to get Pinot cloud-ready, as well as its roadmap to Apache Incubator graduation.")
![[StackUp] TimescaleDB: Performant Time-series Data Management and Analytics with PostgresSQL](https://i.ytimg.com/vi/M59dAS_zjjg/mqdefault.jpg "[StackUp] TimescaleDB: Performant Time-series Data Management and Analytics with PostgresSQL
During this July 2019 meetup at Uber’s New York City office, Matvey Arye of Timescale discusses the advantages of building TimescaleDB as an extension of open source PostgreSQL.")
