Karthik Ramasamy presents the design and implementation of Heron, the new de facto stream data processing engine at Twitter. Ramasamy shares Twitter’s experience of running Heron in production.
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.
Gian Merlino discusses stream processors and a common use case - keeping databases up to date-, the challenges they present, with examples from Kafka, Storm, Samza, Druid, and others.
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.
Ali Kheyrollahi uses clustering and network analysis algorithms to analyze the publicly available Wiki data on rock music to find mathematical relationship between artists, trends and subgenres.
John T Davies is using Spring Integration and Spring Boot to ingest gigabytes of complex data into two different in-memory data grids (IMDGs), showing the design and implementation with several demos.
Joe Stein makes an introduction for developers about why and how to use Apache Kafka. Apache Kafka is a publish-subscribe messaging system rethought of as a distributed commit log.
Michael Ploed talks about the distributed data management challenges that arise in a microservices architecture and how they can be solved using event sourcing in an event-driven architecture.
Howard Chu discusses the Lightning Memory-Mapped Database (LMDB) design and architecture, and its impact on other projects such as OpenLDAP.
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.
Yongsheng Wu talks about how to build highly-resilient systems at scale. Wu presents also failure cases that prompted engineers at Pinterest to build such systems, and how they test these systems.