InfoQ Homepage Database Content on InfoQ
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High Speed Smart Data Ingest into Hadoop
Oleg Zhurakousky discusses architectural tradeoffs and alternative implementations of real-time high speed data ingest into Hadoop.
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Making the Internet a Better Place: Scaling AppNexus
Mike Nolet shares lessons learned scaling AppNexus and architectural details of their system processing 30TB/day: Hadoop, DNS built in GSLB and Keepalived, and real-time data streaming built in C.
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Apache Drill - Interactive Query and Analysis at Scale
Michael Hausenblas introduces Apache Drill, a distributed system for interactive analysis of large-scale datasets, including its architecture and typical use cases.
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MySQL Usage of Web Applications with 1 User and 100 Million
Peter Boros discusses a MySQL architecture useful for the majority of projects, backup, online schema changes, reliability and scalability issues, and basics of sharding.
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A Little Graph Theory for the Busy Developer
Jim Webber explains how to understand the forces and tensions within a graph structure and to apply graph theory in order to predict how the graph will evolve over time.
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A Guide to Python Frameworks for Hadoop
Uri Laserson reviews the different available Python frameworks for Hadoop, including a comparison of performance, ease of use/installation, differences in implementation, and other features.
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Evolving Panorama of Data
Rebecca Parsons reviews some of the changes in how data is used and analyzed, looking at how data is used to track violence, and attempts to predict famine and other crises before they happen.
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Leveraging Scriptable Infrastructures, Towards a Paradigm Shift in Software for Data Science
Karim Chine introduces Elastic-R, demonstrating some of its applications in bioinformatics and finance.
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Amazon DynamoDB Design Patterns & Best Practices
Siva Raghupathy discusses DynamoDB Design Patterns & Best Practices for realizing DynamoDB benefits at the right cost.
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How Draw Something Scaled To 50 million New Users, in 50 Days, with Zero Downtime
Robin Johnson discusses using a data management model for games that can be scaled, and the bottlenecks and challenges met by OMGPOP scaling to millions of users.
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How a Graph Database Allows Shutl to Deliver Even Faster
Volker Pacher explains why Shutl chose Neo4j when faced with the need of building a new API meant to support business growth, the challenges met during implementation and solutions applied.
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Approximate Methods for Scalable Data Mining
Andrew Clegg overviews methods and provides use cases for performing data sets operations like membership testing, distinct counts, and nearest-neighbour finding more efficiently.
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