InfoQ Homepage Streaming Content on InfoQ
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Announcing Broadway
José Valim discusses how Broadway connects multiple stages and producers, how it leverages GenStage to provide back-pressure, and other features such as batching, rate-limiting, partitioning and more.
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A Dive into Streams @LinkedIn with Brooklin
Celia Kung talks about Brooklin, LinkedIn’s managed data streaming service, and dives deeper into its architecture and use cases, as well as their future plans.
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Streaming Log Analytics with Kafka
Kresten Thorup discusses how and why they use Kafka internally and demos how they utilize it as a straightforward event-sourcing model for distributed deployments.
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Massive Scale Anomaly Detection Framework
Guy Gerson introduces an anomaly detection framework PayPal uses, focusing on flexibility to support different types of statistical and ML models, and inspired by scikit-learn and Spark MLlib.
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Building Cloud-Native Data-Intensive Applications with Spring
Sabby Anandan and Soby Chako discuss how Spring Cloud Stream and Kafka Streams can support Event Sourcing and CQRS patterns.
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Next Generation MongoDB: Sessions, Streams, Transactions
Christoph Strobl, Jeff Yemin discuss some of the features in latest MongoDB versions: sessions, change streams, retriable writes, reactive access and transactions.
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The Whys and Hows of Database Streaming
Joy Gao talks about how database streaming is essential to WePay's infrastructure and the many functions that database streaming serves.
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Patterns of Streaming Applications
Monal Daxini talks about streaming application patterns and anti-patterns, and use cases and concrete examples using Apache Flink.
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Streaming SQL to Unify Batch & Stream Processing w/ Apache Flink @Uber
Shuyi Chen and Fabian Hueske explore SQL’s role in the world of streaming data and its implementation in Apache Flink and covering streaming semantics, event time, and incremental results.
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Reactive Front-Ends with RxJS and Angular
Sergi Almar introduces the fundamentals of RxJS, explaining how to manage data streams like UI events, async HTTP requests, and WebSockets / SSE in a uniform way.
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Streaming Reactive Systems & Data Pipes w. Squbs
Anil Gursel and Akara Sucharitakul focus on modeling and building software that considers all input and all output as stream of events, and introducing Squbs.
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Streaming SQL Foundations: Why I ❤ Streams+Tables
Tyler Akidau explores the relationship between the Beam Model and stream & table theory and explains what is required to provide robust stream processing support in SQL.
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