InfoQ Homepage Database Content on InfoQ
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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.
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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.
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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.
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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.
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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.
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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.
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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.
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The Lightning Memory-mapped Database
Howard Chu discusses the Lightning Memory-Mapped Database (LMDB) design and architecture, and its impact on other projects such as OpenLDAP.
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Supercharging Operations and Analytics: Using Spring XD to Support Analytics and CEP
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.
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Building Highly-resilient Systems at Pinterest
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.
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Building a Next-generation Cloud e-Commerce Platform with Spring
Petar Tahchiev demos a typical e-commerce project with the Nemesis platform, listing the problems faced and the Spring projects used: Data, Session, Cloud, Boot, MVC, Security, etc.
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Apache Spark for Big Data Processing
Ilayaperumal Gopinathan and Ludwine Probst discuss Spark and its ecosystem, in particular Spark Streaming and MLlib, providing a concrete example, and showing how to use Spark with Spring XD.
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