InfoQ Homepage Database Content on InfoQ
-
Understanding Real-time Conversations on Facebook
Janet Wiener discusses using a data pipeline and graphic visualizations to extract and analyze the Chorus – the aggregated, anonymized voice of the people communicating on Facebook - in real time.
/presentations/facebook-real-time-conversations/en/mediumimage/Jabig.JPG)
-
Real-time Stream Computing & Analytics @Uber
Sudhir Tonse discusses using stream processing at Uber: indexing and querying of geospatial data, aggregation and computing of streaming data, extracting patterns, TimeSeries analyses and predictions.
/presentations/real-time-streaming-uber/en/mediumimage/Sudbig.JPG)
-
Stream Processing with Apache Flink
Robert Metzger provides an overview of the Apache Flink internals and its streaming-first philosophy, as well as the programming APIs.
/presentations/stream-processing-apache-flink/en/mediumimage/Robig.JPG)
-
Flying Faster with Heron
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.
/presentations/twitter-heron/en/mediumimage/Kabig.JPG)
-
Rethinking Streaming Analytics for Scale
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.
/presentations/stream-analytics-scalability/en/mediumimage/Helbig.JPG)
-
Connecting Stream Processors to Databases
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.
/presentations/stream-processors-databases/en/mediumimage/Giabig.JPG)
-
Node4J: Running Node.js in a JavaWorld
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.
/presentations/node4j-nodejs-java/en/mediumimage/Ianbig.JPG)
-
Real-Time Fraud Detection with Graphs
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.
/presentations/graph-fraud-detection/en/mediumimage/Jimbig.JPG)
-
Insights from History of Rock Music via Machine Learning
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.
/presentations/rock-music-machine-learning/en/mediumimage/Alibig.JPG)
-
Microservices to FastData in the Enterprise with Spring
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.
/presentations/microservices-spring-boot-integration/en/mediumimage/Jobig.JPG)
-
Developing Real-time Data Pipelines with Apache Kafka
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.
/presentations/kafka-real-time-data-pipelines/en/mediumimage/Joebig.JPG)
-
Building Microservices with Event Sourcing and CQRS
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.
/presentations/microservices-event-sourcing-cqrs/en/mediumimage/Micbig.JPG)