Pat Patterson and Ted Malaska talk about current and emerging data processing technologies, and the various ways of achieving "at least once" and "exactly once" timely data processing.
Matthew Sackman discusses dependencies between transactions, how to capture these with Vector Clocks, how to treat Vector Clocks as a CRDT, and how GoshawkDB uses them for a distributed data store.
Adam Miskiewicz goes beyond the React Native docs and talks about best practices for building responsive and production-ready React Native applications with Redux, Relay, and GraphQL.
Helena Edelson addresses new architectures emerging for large scale streaming analytics based on Spark, Mesos, Akka, Cassandra and Kafka (SMACK) or Apache Flink or GearPump.
Ian Bull introduces Node4J and explores the performance characteristics and highlights the tools that help one develop, debug and deploy Node.JS applications running directly on the JVM.
Jim Webber talks about several kinds of fraud common in financial services and how each decomposes into a straightforward graph use-case. He explores them using Neo4j and Cypher query language.
Joseph Paulchell discusses the journey from batch-oriented processes using databases to a real-time data streaming solution and the significant benefits achieved as well as the challenges encountered.
Paul King reviews the features in Groovy which make it easy to work with databases - Groovy SQL, datasets -, and working with NoSQL databases such as MongoDB and Neo4J.
Christoph Strobl focuses on integrating search solutions like Solr, Elasticsearch as well as MongoDBs full text search into an application.
R Tsang shows how to create a Java-based microservice using Spring Boot, containerize it using Maven plugins and deploy a fleet of microservices and dependent components such as Redis using Kubernetes
Bob Familiar introduces microservices, discussing their architecture and outlining cloud deployment scenarios, exemplified by a live demo on Microsoft Azure.
Yan Cui shares lessons learned using Neo4j to model the in-game economy of the "Here Be Monsters" game and automate the balancing process.