NoSQL: A Definition of Big Data

A Definition of Big Data

By Forresters Boris Evelson and Brian Hopkins:

tags:BigData

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NoSQL: A Few More SQLish Statements

A Few More SQLish Statements

A few more statements:

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NoSQL: Common and Recommended Approaches to Cope With Big Data Explosion

Common and Recommended Approaches to Cope With Big Data Explosion

Jorge Lopez:

tags:BigData

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NoSQL: Tutorial: Building Interactive Maps With Polymaps, TileStach, and MongoDB

Tutorial: Building Interactive Maps With Polymaps, TileStach, and MongoDB

A three part tutorial on using MongoDB, PostgreSQL/PostGIS, and Javascript libraries for building interactive maps by Hans Kuder:

tags:MongoDB

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NoSQL: Apache CouchDB 1.0.2: Maintenance Release

Apache CouchDB 1.0.2: Maintenance Release

A new maintenance release from CouchDB:

tags:CouchDB

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NoSQL: NoSQL Screencast: Android Couchbase Tutorial

NoSQL Screencast: Android Couchbase Tutorial

A 12 minutes screencast introducing the basics of Couchbase Mobile for Android applications:

tags:Couchbase

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NoSQL: Running MongoDB on the Cloud

Running MongoDB on the Cloud

I've been posting a lot about deployments in the cloud and especially about deploying MongoDB in the Amazon cloud:

tags:MongoDB

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NoSQL: Paper: Graph Based Statistical Analysis of Network Traffic

Paper: Graph Based Statistical Analysis of Network Traffic

Published by a group from Los Alamos National Lab (Hristo Djidjev, Gary Sandine, Curtis Storlie, Scott Vander Wiel):

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NoSQL: Is Red Hat Interested in the Database Market?

Is Red Hat Interested in the Database Market?

Jim Whitehurst (Red Hat CEO):

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NoSQL: What Are the Goals of BSON?

What Are the Goals of BSON?

Fast scan-ability . For very large JSON documents, scanning can be slow. To skip a nested document or array we have to scan through the intervening field completely. In addition as we go we must count nestings of braces, brackets, and quotation marks. In BSON, the size of these elements is at the beginning of the field's value, which makes skipping an element easy. Easy manipulation . We want to be able to modify information within a document efficiently. Additional data types . JSON is potentially a great interchange format, but it would be nice to have a a few more data types. Most importantly is the addition of a "byte array" data type. This avoids any need to do base64 encoding, which is awkward.

tags:MongoDB

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NoSQL: Monitoring Riak Using Circonus

Monitoring Riak Using Circonus

Denish Patel:

tags:Riak

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NoSQL: HBase and Hadoop at Infolinks

HBase and Hadoop at Infolinks

A while ago I've read in a PR announcement about Infolinks', an in-text advertising company, usage of Hadoop and HBase. Lior Schachter [1] , Infolinks Software Architect, has been kind to answer my questions.

tags:HBase,Hadoop

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NoSQL: Powered by Redis: PUMA.com

Powered by Redis: PUMA.com

Puma.com and other related web properties are using Redis' hashes, lists, and sets (sorted and unsorted) for fragment caching and third party responses caching:

tags:Redis,Memcached

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NoSQL: Pig 0.9: New Features Documented

Pig 0.9: New Features Documented

Three great posts on the Hortonworks' blog, part 1 , part 2 , and part 3 , detailing the most important new features included with the Apache Pig 0.9 release:

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NoSQL: Cloudera Hadoop Distribution on Dell's Commodity Servers

Cloudera Hadoop Distribution on Dell's Commodity Servers

Given:

tags:Hadoop

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NoSQL: Implement Closure Tables for Hierarchical Data in Redis

Implement Closure Tables for Hierarchical Data in Redis

Interesting question raised by Hugo on the Redis group about modeling closure tables [1] in Redis. Didier Spezia offers a solution based on sorted sets.

tags:Redis

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NoSQL: 1 Week, 1 Project, 3 Databases: MarkLogic, CouchDB, MongoDB

1 Week, 1 Project, 3 Databases: MarkLogic, CouchDB, MongoDB

That's the gist of this application. It is non-trivial and had a very rich design and interaction. My team had an excellent QA, excellent front end dev, and me who was the only one who knew MarkLogic. The other team chose to implement theirs using a Javascript front-end architecture communicating with CouchDB (later Java with MongoDB) on the backend. The two teams involved very skilled people. If these two technology approaches were going to go head-to-head, these were the people to do it.

tags:CouchDB,MongoDB

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NoSQL: Memcached in the Cloud: Amazon ElastiCache

Memcached in the Cloud: Amazon ElastiCache

Amazon announced today a new service Amazon ElastiCache or Memcached in the cloud. The new service is still in beta and available only in the US East (Virginia) Region.

tags:Memcached

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NoSQL: Spring Data Graph 1.1.0 Released

Spring Data Graph 1.1.0 Released

Spring Data continues its march to "be all do all":

tags:Neo4j

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NoSQL: The Potential of Big Data Infographic

The Potential of Big Data Infographic

There's no new data in this infographic about BigData, but the amount of stored data by sector is very interesting:

tags:BigData

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NoSQL: Minimalistic CouchDB Client for node.js

Minimalistic CouchDB Client for node.js

Nuno Job's NanoCouch Node.js driver for CouchDB:

tags:CouchDB

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NoSQL: MongoDB 1.8.3 Bugfix Release

MongoDB 1.8.3 Bugfix Release

MongoDB 1.8.3 has been pushed out minutes ago and it includes just a couple of small bug fixes and improvements :

tags:MongoDB

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NoSQL: 1 Trillion RDF Triples With Franz's AllegroGraph

1 Trillion RDF Triples With Franz's AllegroGraph

Patrick Durusau mentioned on his blog a new record set by Franz's AllegroGraph: 1 trillion RDF triples . This comes only 2 months after the previous Franz's AllegroGraph record of 310 billion triples .

tags:AllegroGraph

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NoSQL: The Enterprise Opportunity of Big Data: Closing the "Clue Gap"

The Enterprise Opportunity of Big Data: Closing the "Clue Gap"

Dion Hinchcliffe's excellent article analysing the complexity and the opportunities of Big Data:

tags:BigData

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NoSQL: 40% Penetration for NoSQL: An Interview With Basho's CEO Don Rippert

40% Penetration for NoSQL: An Interview With Basho's CEO Don Rippert

Don Rippert interviewed by Derrick Harris (GigaOm):

tags:Riak,BigData

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NoSQL: Why Big Data Is Such a Hot Topic in the World of Data Management?

Why Big Data Is Such a Hot Topic in the World of Data Management?

Dave Kellogg [1] :

tags:BigData

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NoSQL: Reliable, Scalable, and Kinda Sorta Cheap: A Cloud Hosting Architecture for MongoDB

Reliable, Scalable, and Kinda Sorta Cheap: A Cloud Hosting Architecture for MongoDB

Using MongoDB replicate sets:

tags:MongoDB

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NoSQL: How to Create an Alfred Extension

How to Create an Alfred Extension

David Ferguson:

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NoSQL: Petabytes on a Budget V2.0: Backblaze Storage

Petabytes on a Budget V2.0: Backblaze Storage

It's been over a year since Backblaze revealed the designs of our first generation (67 terabyte) storage pod. During that time, we've remained focused on our mission to provide an unlimited online backup service for $5 per month. To maintain profitability, we continue to avoid overpriced commercial solutions, and we now build the Backblaze Storage Pod 2.0: a 135-terabyte, 4U server for $7,384. It's double the storage and twice the performance—at lower cost than the original.

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NoSQL: CouchDB and DDD

CouchDB and DDD

Bradley Holt:

tags:CouchDB

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NoSQL: Top 5 Priorities of BI Professionals

Top 5 Priorities of BI Professionals

Bob Zurek lists the top 5 priorities of BI people:

tags:BigData

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NoSQL: Bulk Importing Data Into HBase

Bulk Importing Data Into HBase

One such method is a tool called Scoop that automatically imports data between these formats, given schema of both source and destination. We did some in depth research on this tool and concluded it could work well if you have relational data. In addition to this tool Map/Reduce allows various other options including a bulk import method. Bulk Importing bypasses the HBase API and writes contents, which are properly formatted as HBase data files - HFiles, directly to the file system. […] There are two steps involved in Bulk Import Preparing Data (HFiles) using Map/Reduce Importing Prepared Data into HBase table

tags:HBase,Hadoop,MapReduce

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NoSQL: Techmemed: NoSQL Is a Premature Optimization

Techmemed: NoSQL Is a Premature Optimization

This article by Bob Warfield was the first NoSQL post to be Techmemed. Main point:

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NoSQL: Creating a Query DSL Using Clojure and MongoDB

Creating a Query DSL Using Clojure and MongoDB

Christopher Maier:

tags:MongoDB

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NoSQL: How You Should Go About Learning NoSQL

How You Should Go About Learning NoSQL

Yesterday I tweeted three simple rules to learning NoSQL. […] The rules are: 1: Use MongoDB. 2: Take 20 minute to learn Redis 3: Watch this video to understand Dynamo.

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NoSQL: The 5 Phases of Big Data Adoption

The 5 Phases of Big Data Adoption

Denial. Resistance. Acceptance. Embrace. Survival.

tags:BigData

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NoSQL: Data Integrity in the Cloud

Data Integrity in the Cloud

Chris Marsh:

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NoSQL: Hoop - Hadoop HDFS Over HTTP

Hoop - Hadoop HDFS Over HTTP

Cloudera has created a set of tools named Hoop allowing access through HTTP/S to HDFS. My first question was why would you use HTTP to access HDFS? Here is the answer:

tags:Hadoop

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NoSQL: Deploying Cassandra With Puppet

Deploying Cassandra With Puppet

Cassandra is a peer-to-peer architecture which is typically deployed on a large number of servers. Deploying, managing, and upgrading these systems by is more administrative time especially as your cluster grows. Puppet provides a simple way to install Cassandra.

tags:Cassandra

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NoSQL: What's New in Redis 2.4

What's New in Redis 2.4

In short:

tags:Redis

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NoSQL: MongoDB and Amazon: Why EBS?

MongoDB and Amazon: Why EBS?

After linking to the MongoDB in the Amazon cloud , MongoDB and EC2 and the older MongoDB on Amazon EC2 with EBS volumes , Arnout Kazemier commented:

tags:MongoDB

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NoSQL: The Stories of the Revamped Riak Java Client and Improvements in Python Client

The Stories of the Revamped Riak Java Client and Improvements in Python Client

If you read the story of the MongoDB Erlang driver , you'll probably enjoy reading about Riak's revamped Java client or the improvements in the Riak's Python client .

tags:Riak

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NoSQL: Largest MongoDB Databases and Big Data

Largest MongoDB Databases and Big Data

As a follow up to the MongoDB positioning itself as Big Data and development agile environment , I've found this bit of data on Curt Monash's blog [1] :

tags:MongoDB,BigData

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NoSQL: Is Hadoop Our Only Hope?

Is Hadoop Our Only Hope?

Mike Miller [1] naming 3 issues that Hadoop and its ecosystem are facing: investment , data complexity , and

tags:Hadoop,BigData

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NoSQL: CouchDB Isn’t All That Much of a Business

CouchDB Isn't All That Much of a Business

Curt Monash :

tags:CouchDB,Couchbase

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NoSQL: Neo4j Tutorial: The Power of the Daleks

Neo4j Tutorial: The Power of the Daleks

[…] we've built up a Doctor Who data model that shows how Neo4j can be used to address several different data and domain concerns. For example, part of the dataset includes timeline data, comprising seasons, stories and episodes; elsewhere we've social network-like data, with characters connected to one another through being companions, allies or enemies of the Doctor. It's a messy and densely-connected dataset – much like the data you might find in a real-world enterprise. Some of it is of high quality, some of it is lacking in detail. And for every seeming invariant in the domain, there's an awkward exception – again, much like the real world.

tags:Neo4j

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NoSQL: BI Pentaho Integrates Hadoop, NoSQL Databases, and Analytic Databases

BI Pentaho Integrates Hadoop, NoSQL Databases, and Analytic Databases

Dr.Dobb's :

tags:Hadoop,MongoDB

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NoSQL: Sones GraphDB Adds Data Visualization

Sones GraphDB Adds Data Visualization

An interesting addition for the upcoming sones GraphDB 2.1:

tags:sones

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NoSQL: NoSQL: It’s Beginning to Look a Lot Like SQL

NoSQL: It's Beginning to Look a Lot Like SQL

Stephen O'Grady:

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NoSQL: $14mil More for NoSQL Database Couchbase

$14mil More for NoSQL Database Couchbase

Couchbase has raised $14mil in a new round of funding bringing the company's total of capital raised to $30mil. This capital will be used to:

tags:Couchbase

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NoSQL: BigData, Hadoop, and the Impending Informationpocalypse

BigData, Hadoop, and the Impending Informationpocalypse

Even when we do start to be able to integrate and correlate event, configuration, vulnerability or logging data, it's very IT-centric.  It's very INFRASTRUCTURE-centric.  It doesn't really include much value about the actual information in use/transit or the implication of how it's being consumed or related to. The major issue with data "lakes" is that for data to evolve into intelligence and knowledge requires a good understanding of the data itself – how else would one reconcile artifact 'A' with variable 'B' and context 'C' generated from 3 separate data sources .

tags:BigData,Hadoop

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NoSQL: There's No Such Thing as Big Data

There's No Such Thing as Big Data

Alistair Croll:

tags:BigData

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NoSQL: A Beginners' Guide to MongoDB With C#

A Beginners' Guide to MongoDB With C#

Just what the title says.

tags:MongoDB

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NoSQL: Big Data and Emerging NoSQL Databases Shift to Hybrid Database Environments

Big Data and Emerging NoSQL Databases Shift to Hybrid Database Environments

IT decision-makers need to become familiar with the strengths and weaknesses of non-relational systems so they can make informed decisions as to their possible place in the IT infrastructure. The "one size fits all" RDBMS has made database technology decisions relatively easy; in a hybrid future, picking the right database tool may become more complex.

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NoSQL: Parallel Processing Using the Map Reduce Programming Model

Parallel Processing Using the Map Reduce Programming Model

From scripting to MapReduce:

tags:MapReduce,Hadoop

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NoSQL: Riak Tips&Tricks: Streaming List Keys

Riak Tips&Tricks: Streaming List Keys

I'm not sure how long ago I forgot about this, but I just remembered about a nice little feature when I was moving some data around on a Riak cluster. As the post title points out, this feature is streaming list keys in a bucket. […] The useful bit of this is because list_keys can be a lengthy operation, you can begin doing work on the data before you receive all of the keys.

tags:Riak

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NoSQL: Using OCaml From CouchDB Views

Using OCaml From CouchDB Views

Geeky:

tags:CouchDB,MapReduce

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NoSQL: 4 Steps to Solve for Big Data Complex Analysis

4 Steps to Solve for Big Data Complex Analysis

Michael Kaushansky:

tags:BigData

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NoSQL: Running Apache Cassandra 0.8.2 on Windows 7

Running Apache Cassandra 0.8.2 on Windows 7

Alonso Robles:

tags:Cassandra

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NoSQL: Setting Up MongoDB Replica Sets on Amazon EC2

Setting Up MongoDB Replica Sets on Amazon EC2

Zachary Witte:

tags:MongoDB

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NoSQL: Another Redis Use Case: Centralized Logging

Another Redis Use Case: Centralized Logging

Log analysis has become a difficult task in our production environment at work because logs are distributed on different machines and in different files. So, we wanted all the exception logs from all of our apps to be tracked centrally and viewed in single console. And once again, we found another good use case for Redis. Our strategy is to dump all of critical logs in to a Redis List and have a background worker which continuously pulls logs from the Redis List and write stuff in log file.

tags:Redis

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NoSQL: Is Nosql a Premature Optimization That's Worse Than Death? Or the Lady Gaga of the Database World?

Is Nosql a Premature Optimization That's Worse Than Death? Or the Lady Gaga of the Database World?

I was just preparing for a long trip when Michael Stonebraker created a new storm . I only caught Domas Mituzas' sharp reply and Werner Vogel's comment :

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NoSQL: Moving an Elephant: Large Scale Hadoop Data Migration at Facebook

Moving an Elephant: Large Scale Hadoop Data Migration at Facebook

The story of migrating 30PB of HDFS stored data:

tags:Hadoop

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NoSQL: Data Is a Vital Raw Material

Data Is a Vital Raw Material

NYTimes:

tags:BigData

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NoSQL: Building a RSS Feed Processor With Redis

Building a RSS Feed Processor With Redis

A complete example of how prioritization of queues in BLPOP works:

tags:Redis

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NoSQL: CouchDB and Redis: Strengths and Weaknesses

CouchDB and Redis: Strengths and Weaknesses

Knowing the strenghts and weaknesses of each of them could help making a decision. But do not fall for comparing them:

tags:CouchDB,Redis

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NoSQL: blitz.io: How We Use Heroku, AWS and CouchDB

blitz.io: How We Use Heroku, AWS and CouchDB

blitz.io, the winner of the Best CouchDB app :

tags:CouchDB

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NoSQL: What Scales Best?

What Scales Best?

Tony Bain:

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NoSQL: Is NoSQL a Fad or the Future of Managing Data?

Is NoSQL a Fad or the Future of Managing Data?

Tim Anglade about NoSQL:

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NoSQL: Cassandra Query Language: Not Just NoSQL. It's MoSQL

Cassandra Query Language: Not Just NoSQL. It's MoSQL

Cassandra 0.8 included the first version of Cassandra Query Language or CQL . Eric Evans gave a talk at Cassandra SF 2011 introducing Cassandra Query Language as an alternative and not replacement of the current Cassandra API:

tags:Cassandra

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NoSQL: MongoDB Positioning: Big Data and Development Agility

MongoDB Positioning: Big Data and Development Agility

Max Schireson positions MongoDB as a solution for Big Data and development agility:

tags:MongoDB,BigData

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NoSQL: Nimble Storage Innovations

Nimble Storage Innovations

A short video talking about an interesting storage technology from Nimble Storage :

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NoSQL: Twitter Open Sourcing Storm at Strange Loop

Twitter Open Sourcing Storm at Strange Loop

Ask and you'll be answered . Nathan Marz announces that Twitter will open source Storm, the Hadoop-like real-time data processing tool developed at BackType:

tags:Hadoop

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NoSQL: An Alternative Approach for Big Data Real Time Analytics

An Alternative Approach for Big Data Real Time Analytics

Starting from the architecture of Facebook's realtime analytics presented in the paper Apache Hadoop Goes Realtime at Facebook and Dhruba Borthakur's excellent posts HDFS: Realtime Hadoop and HBase Usage at Facebook , Nati Shalom describes an alternative approach for real-time analytics using data grids making the following assumptions:

tags:HBase,BigData

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NoSQL: Addressing the NoSQL Criticism

Addressing the NoSQL Criticism

Bill Karwin's comment is spot on [1] :

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NoSQL: MongoDB Is Cocoafish Best Friend

MongoDB Is Cocoafish Best Friend

Cocoafish's [1] story of going NoSQL started based on this analysis:

tags:MongoDB

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NoSQL: Polyglot Platform

Polyglot Platform

Even if Heroku's post is about polyglot programming and commodifying deployments, many of the points apply to polylgot persistence. Especially this one:

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NoSQL: LevelDB and Kyoto Cabinet Benchmark

LevelDB and Kyoto Cabinet Benchmark

I've been pretty excited about Google's LevelDB, not to mention there are some really old tanks already in the battle field like BDB, Tokyo Cabinet (Kyoto Cabinet as new one), HamsterDB etc. Fortunately I've already worked with Kyoto Cabinet and when I looked at the benchmarks I was totally blown away.

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NoSQL: A Detailed Guide to Oozie

A Detailed Guide to Oozie

Boris Lublinsky and Michael Segel series of articles about Oozie, the Hadoop workflow framework, published on InfoQ:

tags:Hadoop,MapReduce

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NoSQL: LevelDB: Google's Fast Persistent Key-Value Store Library

LevelDB: Google's Fast Persistent Key-Value Store Library

Google open sourced a while ago LevelDB , a C++ library that provides an ordered mapping key-value storage. LevelDB performance convinced Basho guys to experiment with adding LevelDB as a storage engine for Riak . And there's also a benchmark comparing LevelDB with SQLite and Kyoto Cabinet.

tags:Riak

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NoSQL: eBay Deploys 100TB of Flash Storage

eBay Deploys 100TB of Flash Storage

eBay is a prime example of the benefits of flash. Nimbus Data CEO Thomas Isakovich told me that eBay had only 2.5TB of flash installed six months ago before recently upgrading to 100TB. Within the PayPal division, where Nimbus is deployed, Isakovich said eBay has cut power costs by 78 percent, cut its rack space by half and is able to better meet performance demand overall by spinning up virtual machines even faster.

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NoSQL: Where Is the World's Data Stored

Where Is the World's Data Stored

An infographic with the largest data storage centers from Mozy via ReadWriteWeb :

tags:BigData

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NoSQL: blitz.io: Best CouchDB App

blitz.io: Best CouchDB App

The architecture of blitz.io , a geo-distributed load and performance testing service built on top of the CouchDB:

tags:CouchDB

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NoSQL: Inside Match.com

Inside Match.com

The article doesn't get into the technical details [1] , but this sounds like a BigData scenario with offline batch processing, where Hadoop is "the solution":

tags:BigData,Hadoop

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