NoSQL: Monitoring MongoDB

Monitoring MongoDB

The guys from Boxed Ice have already published a lot about their experience running MongoDB in production , plus a series of posts advising on MongoDB monitoring. Actually they are offering a hosted service for MongoDB monitoring: Server Density .

tags:MongoDB

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NoSQL: MongoDB Schema Design Basics

MongoDB Schema Design Basics

For NoSQL databases there are no clear rules like the Boyce-Codd Normal Form database normalization . Data modeling and analysis of data access patterns are two fundamental activities. While over the last 2 years we've gather some recipes, it's always a good idea to check what are the recommended ways to model your data with your choice of NoSQL database.

tags:MongoDB

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NoSQL: Paper: Google Fusion Tables: Data Management, Integration and Collaboration in the Cloud

Paper: Google Fusion Tables: Data Management, Integration and Collaboration in the Cloud

This paper from Google talks extensively about the usage of BigTable and Megastore, the data model, query processing, and transaction handling in the implementation of Google Fusion Tables.

tags:BigTable

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NoSQL: Voldemort V0.9 Released: NIO, Pipelined FSM, Hinted Handoff

Voldemort V0.9 Released: NIO, Pipelined FSM, Hinted Handoff

I rarely have the chance to write about Project Voldemort and this new release packs so many goodies:

tags:Voldemort

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NoSQL: Redis at Causes and a Redis Mock Library

Redis at Causes and a Redis Mock Library

Two interesting things in this post.

tags:Redis

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NoSQL: Someone Is Monetizing Big Data and It Is Not for Our Benefit

Someone Is Monetizing Big Data and It Is Not for Our Benefit

Similarly some of the banks have admitted that they will be mining data related to the transactions we perform to understand our buying behavior. This data can then be sold to retailers or e-marketers to generate specific offers that may suit our lifestyle. It may be creepy to get an e-coupon out of the blue on your birthday (or anniversary) from a retailer that you would have shopped with some time back, but it could also have some nice benefits. On top of that, each one of us leaves behind digital tracks when we search or browse through different sites looking for something on the internet. If such data can be tagged to us, it can demonstrate our common interests.

tags:BigData

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NoSQL: Hadoop Advancing Information Management

Hadoop Advancing Information Management

A summary of a survey run by Ventana about Hadoop:

tags:Hadoop

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NoSQL: HBase at Yfrog

HBase at Yfrog

Even if the Yfrog presentation on their usage of HBase has only 9 slides, you'll find some very interesting notes in there. Here's a couple that caught my eyes:

tags:HBase

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NoSQL: Redis at Bump

Redis at Bump

We have ended up using Redis for a host of other smaller things as we continue to grow. Although this wasn't an explicit decision, Redis provides enough basic data types and functionality to get most problems done and you'd be hard pressed to find something that can do it faster.

tags:Redis

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NoSQL: NoSQL/NewSQL/MySQL Is Not a Zero Sum Game

NoSQL/NewSQL/MySQL Is Not a Zero Sum Game

Although there will be isolated examples, it is going to be rare, therefore, that any potential adopter would be directly comparing NoSQL and NewSQL technologies unless they are still at the stage trying to figure out the level of consistency required for an individual application.

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NoSQL: Time Lines and News Streams: Neo4j Is 377 Times Faster Than MySQL

Time Lines and News Streams: Neo4j Is 377 Times Faster Than MySQL

In my use case neo4j outperformed MySQL by a factor of 377 ! That is more than two magnitudes). As known one part of my PhD thesis is to create a social newsstream application around my social networking site metalcon.de. It is very obvious that a graph structure for social newsstreams are very natural: You go to a user. Travers to all his friends or objects of interest and then traverse one step deeper to the newly created content items. A problem with this kind of application is the sorting by Time or relvance of the content items. But before I discuss those problems I just want to present another comparission between MySQL and neo4j.

tags:Neo4j

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NoSQL: Beyond NoSQL: Using RRD to Store Temporal Data

Beyond NoSQL: Using RRD to Store Temporal Data

Patrick Schless describes the pros of using RRDTool for collect write-once data over time, and graph the results.

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NoSQL: Mongs: Data Browser for MongoDB

Mongs: Data Browser for MongoDB

A read-only web based interface to your MongoDB data:

tags:MongoDB

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NoSQL: DataSift PubSub: From Redis to Kafka and 0mq

DataSift PubSub: From Redis to Kafka and 0mq

DataSift moves from Redis PubSub to Kafka and 0mq  :

tags:Redis

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NoSQL: Hadoop and IBM Netezza: Compete or Co-Exist?

Hadoop and IBM Netezza: Compete or Co-Exist?

I assume people on both sides of data warehouses (users and providers) are asking the same question. IBM Netezza and Cloudera seem to agree on the answer:

tags:Hadoop

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NoSQL: Enterprise Big Data Stack vs Open Source Big Data Stack

Enterprise Big Data Stack vs Open Source Big Data Stack

Goldmacher estimated that YouTube consumption—user uploads of 48 hours of video a minute and 3 billion videos a day along with roughly 45 petabytes of viewed videos a day—would require at least 9 full-rack Exadata machines at $1.5 million each. There would be at least 18 Exadata machines to handle spikes. Those machines would add up to 14 Exalogic devices to serve data at $1.1 million per system. The software stack under Oracle would include WebLogic middleware, Oracle databases, Exadata optimized storage and Oracle as operating system. The open source comparison included JBoss middleware, MySQL, Hadoop and Red Hat Enterprise Linux as the OS.

tags:Hadoop

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NoSQL: The Main Benefits of Riak

The Main Benefits of Riak

Dave Smith [1] about Riak:

tags:Riak

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NoSQL: Neo4j 1.4 “Kiruna Stol” Released With Many Notable Improvements

Neo4j 1.4 "Kiruna Stol" Released With Many Notable Improvements

Releasing often has too many advantages to list them all, but I think the major ones are: capturing the interest of new users (generating buzz), showing a healthy project velocity, and, probably the most important one, delivering the features and improvements users were asking for in a timely manner . Neo4j has learned these lessons [1] and since Neo4j 1.2 the team at Neo Technologies is trying a very frequent release plan which also includes milestone releases. The other day, Neo4j 1.4, a.k.a. Kiruna Stol, has been released:

tags:Neo4j

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NoSQL: The Server Architecture Debate Rages On

The Server Architecture Debate Rages On

Big processors or little processors, scale-up or scale-out, on-premise or in the cloud […] The plethora of choices for application architecture and delivery model are great if you like variety, but I don't envy anyone tasked with choosing which system on which to spend their limited budget dollars.

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NoSQL: Seven Java Projects That Changed the World

Seven Java Projects That Changed the World

Over the last decade, several projects have traveled beyond mere adoption and had effects dominating the Java world, into software development in general, and some even further into the daily lives of users.

tags:Hadoop

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NoSQL: A Preview of Future Disk Drives

A Preview of Future Disk Drives

A new type of data storage technology, called phase-change memory, has proven capable of writing some types of data faster than conventional flash based storage. The tests used a hard drive based on prototype phase-change memory chips.

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NoSQL: Comments on Urban Myths About NoSQL

Comments on Urban Myths About NoSQL

Dan Weinreb comments on Michael Stonebraker's Urban Myths about SQL (PDF)  :

tags:VoltDB

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NoSQL: Best Practices for Data Virtualization

Best Practices for Data Virtualization

Ash Parikh (Informative) interviewed by Linda L. Briggs (tdwi):

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NoSQL: Petabyte-Scale Hadoop Clusters

Petabyte-Scale Hadoop Clusters

Curt Monash quoting Omer Trajman (Cloudera) in a post counting petabyte-scale Hadoop deployments:

tags:Hadoop

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NoSQL: MongoDB Is the New MySQL

MongoDB Is the New MySQL

Stephen O'Grady:

tags:MongoDB

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NoSQL: Big Data and the Semantic Web

Big Data and the Semantic Web

Edd Dumbill:

tags:BigData

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NoSQL: Rethink Your Data Model

Rethink Your Data Model

Karl Seguin [1] :

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NoSQL: The Story of the MongoDB Erlang Driver

The Story of the MongoDB Erlang Driver

Tony Hannan:

tags:MongoDB

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NoSQL: Quick Guide to the Neo4j REST API

Quick Guide to the Neo4j REST API

Pierre Lindenbaum's brief intro to Neo4j REST API:

tags:Neo4j

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NoSQL: What Are the Benefits of Building CouchApps?

What Are the Benefits of Building CouchApps?

Bradley Holt [1] :

tags:CouchDB

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NoSQL: MongoDB Hosting Matrix

MongoDB Hosting Matrix

Maurício Maia put together a price comparison for MongoDB hosting:

tags:MongoDB

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NoSQL: Zynga, Data Centers, Polyglot Persistence, and Big Data

Zynga, Data Centers, Polyglot Persistence, and Big Data

Cadir Lee (CTO Zynga) quoted in a VentureBeat post :

tags:Membase,Hadoop

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NoSQL: The Challenge of Big Data

The Challenge of Big Data

Don DeLoach (CEO Infobright) interviewed by James Powell (tdwi):

tags:BigData

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NoSQL: Business Intelligence for Big Data: What Is Missing?

Business Intelligence for Big Data: What Is Missing?

Eric Rogge:

tags:BigData

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NoSQL: MongoDB Journaling and Replication Interaction

MongoDB Journaling and Replication Interaction

How do we know our data won't be rolled back? The answer is that a write is truly committed in a replica set when it has been written at a majority of set members. We can confirm this with the getLastError command. For example, if our write has made it to the journal on two out of three total set members, we know the data is committed even if nodes fail in a cascading sequence, and even if a minority of nodes are permanently lost.

tags:MongoDB

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NoSQL: NetApp Hadoop Open Storage System

NetApp Hadoop Open Storage System

Did I say everyone wants a piece of Hadoop's future profit?

tags:Hadoop

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NoSQL: Riak Getting LevelDB as Storage Engine

Riak Getting LevelDB as Storage Engine

After Innostore and Bitcask , Basho guys are currently experimenting with integrating Google's LevelDB as a storage engine for Riak. Preliminary results are looking promising:

tags:Riak

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NoSQL: ElephantDB and Storm Join the Twitter Flock

ElephantDB and Storm Join the Twitter Flock

That's to say BackType, creators of Cascalog , ElephantDB , and Storm , has been acquired by Twitter (which in case you didn't know names most of their open source libraries and storage solutions using bird names).

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NoSQL: Big Data Has a Secret

Big Data Has a Secret

Nicholas Goodman's (LucidDB) sharp vision about Business Intelligence on Big Data:

tags:BigData

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NoSQL: Big Data: Volume vs Variety According to McKinsey and Gartner

Big Data: Volume vs Variety According to McKinsey and Gartner

The value of "big data" lies less in its volume than in its variety. This is the gist of a recent report from the McKinsey Global Institute, Big data: The next frontier for innovation, competition, and productivity. […] On the vendors' side of the house, Stephen Brobst, Teradata's chief technology officer, has told us: "It's not actually the size of the data that matters as much as the diversity. One important factor is the transition from transactions to interactions. This creates big data."

tags:BigData

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NoSQL: CouchDB Queue Service: Amazon SQS API-compatible

CouchDB Queue Service: Amazon SQS API-compatible

Neat idea that could prove pretty useful in development environments:

tags:CouchDB

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NoSQL: An Intro to Gremlin the Graph Traversal Language

An Intro to Gremlin the Graph Traversal Language

A nice intro to Gremlin , the Groovy-based graph traversal language supporting Neo4j, OrientDB, DEX, RDF Sail, TinkerGraph, and ReXster:

tags:Neo4j,OrientDB

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NoSQL: Document Databases: Documents, Nothing but Documents

Document Databases: Documents, Nothing but Documents

Roman Stoffel published a great intro to documents from the perspective of document databases. While the code is specific to RavenDB, most of the principles exposed apply to all document databases. If you didn't work with a document database, like RavenDB, MongoDB, CouchDB, make sure you check this post.

tags:RavenDB,MongoDB,CouchDB

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NoSQL: SQL Access to CouchDB Views : Easy Reporting | Goodman on BI

SQL Access to CouchDB Views : Easy Reporting | Goodman on BI

Nicholas Goodman:

tags:CouchDB

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NoSQL: Human BigData vs Machine BigData

Human BigData vs Machine BigData

Humans vs machines:

tags:BigData

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NoSQL: Aster Data SQL-MapReduce Technology Patent

Aster Data SQL-MapReduce Technology Patent

From a Teradata PR announcement :

tags:MapReduce

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NoSQL: The Single Point of Truth Rule: The Most Important Concept in Systems Design

The Single Point of Truth Rule: The Most Important Concept in Systems Design

Ted Dziuba in his effervescent tone:

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NoSQL: Paper: Apache Hadoop Goes Realtime at Facebook

Paper: Apache Hadoop Goes Realtime at Facebook

Links to the most publicized paper of a Hadoop use case, Facebook has presented at SIGMOD 2011: paper and presentation slides :

tags:Hadoop

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NoSQL: Concurrency and Redis

Concurrency and Redis

Santosh Kumar:

tags:Redis

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NoSQL: Hadoop Chaos Monkey: The Fault Injection Framework

Hadoop Chaos Monkey: The Fault Injection Framework

Do you remember the 5 lessons Netflix learned while using the Amazon Web Services —judging by how much Netflix shared about their experience in the cloud including Amazon SimpleDB I'd say these 5 are only the tip of the iceberg—where they talked about the Chaos Monkey ?

tags:Hadoop

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NoSQL: NoSQL Adoption in the Enterprise Environment

NoSQL Adoption in the Enterprise Environment

I've read a couple of reports [1] related to a survey run by Evans Data covering also the adoption of NoSQL databases inside the enteprise world. I could not access the survey nor the results, but all these reports are quoting the following result:

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NoSQL: Backing Up MongoDB: Single Server, Replica Sets, Sharded Cluster

Backing Up MongoDB: Single Server, Replica Sets, Sharded Cluster

For single server deployments, backups are a must. But sometimes you might need to backup other deployments too. After the break, Scott Fernandez' (10gen) talks about backing up a single server MongoDB, MongoDB replica sets, and MongoDB sharded cluster.

tags:MongoDB

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NoSQL: Hadoop Summit 2011 in Review

Hadoop Summit 2011 in Review

For those of us that haven't been at the Hadoop Summit 2011:

tags:Hadoop

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NoSQL: GoldenOrb: Ravel Google Pregel Implementation Released

GoldenOrb: Ravel Google Pregel Implementation Released

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