InfoQ Homepage AI, ML & Data Engineering Content on InfoQ
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How Shutl Delivers Even Faster Using Neo4J
Volker Pacher, Sam Phillips present key differences between relational databases and graph databases, and how they use the later to model a complex domain and to gain insights into their data.
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Enterprise IT: What's Beyond Virtualization
Derek Collison discusses some of the technologies and approaches for building a self-healing infrastructure: Intelligent layer 7 SDN with semantic awareness, self healing techniques, etc.
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Employing Data Science to Enhance the Facebook Experience
Justin Moore shares how Facebook's own advances in Data Science have solved intricate location technology problems and how these lessons can be applied to other verticals to achieve similar gains.
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Have You Seen Spring Lately?
Josh Long introduces some of the latest Spring features supporting HATEOAS-compliant and OAuth-secured REST services, NoSQL and Big Data, Websockets, OAuth, open-web security and mobile.
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Big Data in Capital Markets
The authors present design patterns and use cases of capital market firms that are incorporating big data technologies into their credit risk analysis, price discovery or sentiment analysis software.
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A/B Testing + Continuous Delivery = Everyday Product Launches
Nellwyn Thomas discusses how Etsy is using A/B testing, how Etsy's data-driven culture has evolved over time and how continuous delivery and big data can coexist.
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How Facebook Scales Big Data Systems
Jeff Johnson introduces Apollo, a hierarchical NoSQL data system meant to deal with Facebook's distributed storage needs.
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Migrating to Cloud Native with Microservices
Adrian Cockcroft discusses strategies, patterns and pathways to perform a gradual migration towards modern enterprise applications based on cloud, microservices and denormalized NoSQL databases.
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Analyzing Big Data On The Fly
Shawn Gandhi overviews real-time processing use cases, and how developers are using AWS Kinesis to shift from a traditional batch-oriented approach to a continual real-time data processing model.
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How WebMD Maintains Operational Flexibility with NoSQL
Rajeev Borborah, Matthew Wilson discuss using NoSQL at WebMD -architecture, benefits, roadmap-, with details on caching and key-value storage implementation behind a few of the WebMD applications.
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The Game of Big Data: Scalable, Reliable Analytics Infrastructure at KIXEYE
Randy Shoup describes KIXEYE's analytics infrastructure from Kafka queues through Hadoop 2 to Hive and Redshift, built for flexibility, experimentation, iteration, testability, and reliability.
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Doing Data Science with F#
Tomas Petricek introduces F#’s capabilities in dealing with scientific data: type providers -CSV, XML, JSON, REST-, interactive development, data visualization libraries, integration with R or MathLab
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