InfoQ Homepage NoSQL Content on InfoQ
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Sync is the Future of Mobile Data
Chris Anderson provides code samples on how to build offline applications for mobile platforms based on the NoSQL document model, and how to contribute to the open source projects behind this movement
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How Developers Can Treat Ovarian Cancer
Mridula Jayaraman shares from her experience developing a next generation sequencing solution used to customize cancer treatment based on patient's genetic makeup.
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Making Java Groovy
Ken Kousen advises Java developers how to do similar tasks in Groovy: building and testing applications, accessing both relational and NoSQL databases, accessing web services, and more.
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Building a Multi-Master Distributed Redis in Erlang
Chad DePue presents the process of building Edis, a Redis clone written in Erlang, allowing pluggable backends and implementing the Paxos algorithm.
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Scaling Pinterest
Details on Pinterest's architeture, its systems -Pinball, Frontdoor-, and stack - MongoDB, Cassandra, Memcache, Redis, Flume, Kafka, EMR, Qubole, Redshift, Python, Java, Go, Nutcracker, Puppet, etc.
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Graph Computing at Scale
Matthias Broecheler discusses graph computing, introducing the Aurelius graph cluster enabling graph computing at scale by building on distributed systems like Cassandra, HBase, and Hadoop.
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Tracking Millions of Ganks in Near Real Time
Garrett Eardley explores how Riot Games is using Riak for their stats system, discussing why they chose Riak, the data model and indexes, and strategies for working with eventually consistent data.
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Spanner - Google's Distributed Database
Sebastian Kanthak details how Spanner relies on GPS and atomic clocks to provide two of its innovative features: Lock-free strong reads and global snapshots consistent with external events.
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Working with Databases and Groovy
Paul King presents working with databases in Groovy, covering datasets, GMongo, Neo4J, raw JDBC, Groovy-SQL, CRUD, Hibernate, caching, Spring Data technologies, etc.
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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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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 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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