NoSQL: Where Does Xeround Fit In The Cap Theorem?

Where Does Xeround Fit In The Cap Theorem?

Itamar Haber over the Xeround blog:

tags:xeround,cap,mysql,database as a service,daas

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NoSQL: Vertica and Hadoop for Big Data

Vertica and Hadoop for Big Data

Here is what I've jotted down during Vertica's webinar Hadoop vs. RDBMS for Big Data Analytics: Why Choose?

tags:vertica,hadoop,bigdata

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NoSQL: NoSQL Tutorial: Setting Up a Hadoop Cluster with MongoDB Support on EC2

NoSQL Tutorial: Setting Up a Hadoop Cluster with MongoDB Support on EC2

A complete and detailed guide for setting up a Hadoop cluster using MongoDB by Arten Yankov. It uses the MongoDB Hadoop adapter mongo-hadoop , which provides input and output adapters, support for InputSplits, and write-only Pig.

tags:hadoop,mongodb,aws,ec2,nosql library

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NoSQL: 5 Key Elements for a Firehose Data System

5 Key Elements for a Firehose Data System

The 5 key elements for a firehose data system as per a presentation by Josh Berkus, CEO of PostgreSQL Experts Inc. summarized by Brian Proffitt on ITworld :

tags:nosql theory,bigdata

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NoSQL: MongoDB Tips and Tricks: More Reads Make For Faster Writes

MongoDB Tips and Tricks: More Reads Make For Faster Writes

The trick to lowering your lock percentage and thus having faster updates is to query the document you are going to update, before you perform the update. Querying before doing an upsert might seem counter intuitive at first glance, but it makes sense when you think about it. The read ensures that whatever document you are going to update is in RAM. This means the update, which will happen immediately after the read, always updates the document in RAM, which is super fast. I think of it as warming the database for the document you are about to update.

tags:mongodb

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