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Druid at Netflix

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@ -188,7 +188,7 @@ An updated and organized reading list for illustrating the patterns of scalable,
* [Scheduler at Nextdoor](https://engblog.nextdoor.com/we-don-t-run-cron-jobs-at-nextdoor-6f7f9cc62040)
* [Peloton: Unified Resource Scheduler for Diverse Cluster Workloads at Uber](https://eng.uber.com/peloton/)
* [Fenzo: OSS Scheduler for Apache Mesos Frameworks at Netflix](https://medium.com/netflix-techblog/fenzo-oss-scheduler-for-apache-mesos-frameworks-5c340e77e543)
* [Airflow](https://airflow.apache.org/)
* [Airflow - Workflow Orchestration](https://airflow.apache.org/)
* [Airflow at Airbnb](https://medium.com/airbnb-engineering/airflow-a-workflow-management-platform-46318b977fd8)
* [Airflow at Pandora](https://engineering.pandora.com/apache-airflow-at-pandora-1d7a844d68ee)
* [Airflow at Robinhood](https://robinhood.engineering/why-robinhood-uses-airflow-aed13a9a90c8)
@ -271,7 +271,7 @@ An updated and organized reading list for illustrating the patterns of scalable,
* [Wormhole: Pub-Sub System at Facebook](https://code.facebook.com/posts/188966771280871/wormhole-pub-sub-system-moving-data-through-space-and-time/)
* [Pub-Sub in Chatting Architecture at LINE](https://engineering.linecorp.com/en/blog/detail/85)
* [Pub-Sub in Microservices at Netflix](https://medium.com/netflix-techblog/how-netflix-microservices-tackle-dataset-pub-sub-4a068adcc9a)
* [Kafka the Message Broker](https://martin.kleppmann.com/papers/kafka-debull15.pdf)
* [Kafka - Message Broker](https://martin.kleppmann.com/papers/kafka-debull15.pdf)
* [Kafka at LinkedIn](https://engineering.linkedin.com/kafka/running-kafka-scale)
* [Kafka at Pinterest](https://medium.com/pinterest-engineering/how-pinterest-runs-kafka-at-scale-ff9c6f735be)
* [Kafka at Trello](https://tech.trello.com/why-we-chose-kafka/)
@ -448,10 +448,11 @@ An updated and organized reading list for illustrating the patterns of scalable,
* [Roshi: Distributed Storage System for Time-Series Event at SoundCloud](https://developers.soundcloud.com/blog/roshi-a-crdt-system-for-timestamped-events)
* [Goku: Time Series Database at Pinterest](https://medium.com/@Pinterest_Engineering/goku-building-a-scalable-and-high-performant-time-series-database-system-a8ff5758a181)
* [Scaling Time Series Data Storage (2 parts) at Netflix](https://medium.com/netflix-techblog/scaling-time-series-data-storage-part-ii-d67939655586)
* [Real-time Analytics Database (Druid)](https://druid.apache.org/)
* [Druid - Real-time Analytics Database](https://druid.apache.org/)
* [Druid at Airbnb](https://medium.com/airbnb-engineering/druid-airbnb-data-platform-601c312f2a4c)
* [Druid at Walmart](https://medium.com/walmartlabs/event-stream-analytics-at-walmart-with-druid-dcf1a37ceda7)
* [Druid at eBay](https://tech.ebayinc.com/engineering/monitoring-at-ebay-with-druid/)
* [Druid at Netflix](https://netflixtechblog.com/how-netflix-uses-druid-for-real-time-insights-to-ensure-a-high-quality-experience-19e1e8568d06)
* [Distributed Repositories, Dependencies, and Configurations Management](https://betterexplained.com/articles/intro-to-distributed-version-control-illustrated/)
* [DGit: Distributed Git at Github](https://githubengineering.com/introducing-dgit/)
* [Stemma: Distributed Git Server at Palantir](https://medium.com/@palantir/stemma-distributed-git-server-70afbca0fc29)