ALL COVERED TOPICS

NoSQL Benchmarks NoSQL use cases NoSQL Videos NoSQL Hybrid Solutions NoSQL Presentations Big Data Hadoop MapReduce Pig Hive Flume Oozie Sqoop HDFS ZooKeeper Cascading Cascalog BigTable Cassandra HBase Hypertable Couchbase CouchDB MongoDB OrientDB RavenDB Jackrabbit Terrastore Amazon DynamoDB Redis Riak Project Voldemort Tokyo Cabinet Kyoto Cabinet memcached Amazon SimpleDB Datomic MemcacheDB M/DB GT.M Amazon Dynamo Dynomite Mnesia Yahoo! PNUTS/Sherpa Neo4j InfoGrid Sones GraphDB InfiniteGraph AllegroGraph MarkLogic Clustrix CouchDB Case Studies MongoDB Case Studies NoSQL at Adobe NoSQL at Facebook NoSQL at Twitter

NAVIGATE MAIN CATEGORIES

Close

Neo4j: All content tagged as Neo4j in NoSQL databases and polyglot persistence

Neo4j and D3.js: Visualizing Connections Over Time

Another great graph data visualization using Neo4j and D3.js from Max De Marzi:

Graph data visualization of connections over time

  • Max de Marzi is lately my favorite source for graph data visualization posts
  • Even if the diagram looks amazing I’m wondering if it would scale for larger data sets
  • Even if I gave it some thought, I’m still not sure how graph databases can record historical relationship/the evolution of relationships in a graph. If you have any ideas I’d love to hear.

Original title and link: Neo4j and D3.js: Visualizing Connections Over Time (NoSQL database©myNoSQL)


Neo4j and JRuby: Expressive Graph Traversals With Jogger

Jogger gives you named traversals and is a little bit like named scopes. Jogger groups multiple pacer traversals together and give them a name. Pacer traversals are are like pipes. What are pipes? Pipes are great!!

The most important conceptual difference is, that the order in which named traversals are called matter, while it usually doesn’t matter in which order you call named scopes.

Knowing how Gremlin and Cypher compare, question is how is Jogger compared to Cypher?

Original title and link: Neo4j and JRuby: Expressive Graph Traversals With Jogger (NoSQL database©myNoSQL)


Beer Recommendations With Graph Databases

Josh Adell explains how to extend a simple recommendation engine to similarity-based collaborative filtering:

Instead of basing recommendations off of one similar rating, I can calculate how similarly you and I rated all the things we have rated, and only get recommendations from you if I have determined we are similar enough in our tastes.

This is much closer to how recommendation engines developed by sites like Amazon or Netflix are working.

Original title and link: Beer Recommendations With Graph Databases (NoSQL database©myNoSQL)

via: http://blog.everymansoftware.com/2012/02/similarity-based-recommendation-engines.html


Gremlin vs Cypher

Romiko Derbynew comparing Gremlin and Neo4j Cypher:

  • Simple graph traversals are much more efficient when using Gremlin
  • Queries in Gremlin are 30-50% faster for simple traversals
  • Cypher is ideal for complex traversals where back tracking is required
  • Cypher is our choice of query language for reporting
  • Gremlin is our choice of query language for simple traversals where projections are not required
  • Cypher has intrinsic table projection model, where Gremlins table projection model relies on AS steps which can be cumbersome when backtracking e.g. Back(), As() and _CopySplit, where cypher is just comma separated matches
  • Cypher is much better suited for outer joins than Gremlin, to achieve similar results in gremlin requires parallel querying with CopySplit, where as in Cypher using the Match clause with optional relationships
  • Gremlin is ideal when you need to retrieve very simple data structures
  • Table projection in gremlin can be very powerful, however outer joins can be very verbose

So in a nutshell, we like to use Cypher when we need tabular data back from Neo4j and is especially useful in outer joins.

Patrick Durusau

Original title and link: Gremlin vs Cypher (NoSQL database©myNoSQL)

via: http://romikoderbynew.com/2012/02/22/gremlin-vs-cypher-initial-thoughts-neo4j/


Neo4J Spatial and Gephi for Smart Data Analysis

As I often run the same course, it would be interesting to calculate my average pace at specific locations. When combining the data of all of my courses, I could deduct frequently encountered locations. Finally, could there be a correlation between my average pace and my distance from home? In order to come up with answers to these questions, I will import my running data into a Neo4J Spatial datastore. Neo4J Spatial extends the Neo4J Graph Database with the necessary tools and utilities to store and query spatial data in your graph models. For visualizing my running data, I will make use of Gephi, an open-source visualization and manipulation tool that allows users to interactively browse and explore graphs.

This looks like a great application of a graph database for analyzing geo data. And it’s very practical.

Original title and link: Neo4J Spatial and Gephi for Smart Data Analysis (NoSQL database©myNoSQL)

via: http://datablend.be/?p=1255&mkt_tok=3RkMMJWWfF9wsRonuKzKZKXonjHpfsX56%2BsrXaOg38431UFwdcjKPmjr1YAFTtQhcOuuEwcWGog8zglXDuWWdI5P9vpaEg%3D%3D


A Question About NoSQL Managed Hosting

It’s impossible to always have the right answers to all the questions. So this time I’ll have to ask you all: why only some NoSQL databases are present in managed hosting offers?

The first wave of NoSQL managed hosting services brought MongoDB, CouchDB, and some Redis. The second wave brought some more MongoDB, CouchDB, and just a bit more of Redis. It was only the third wave that brought some managed services for graph databases: Neo4j and OrientDB. Plus the first proposal for Cassandra managed hosting.

The first answer that comes to mind when thinking about NoSQL managed services is adoption. If a product is not in wide use then the chances for a company to run a profitable hosting business are very low. But I have the feeling that this is not the only or the complete answer.

Please chime in and share your thoughts.

Original title and link: A Question About NoSQL Managed Hosting (NoSQL database©myNoSQL)


What types of applications might a graph database be well suited for?

Found this list of use cases for graph databases in a follow up of a Neo4j webinar:

  • Social networks
  • Collaboration programs
  • Configuration Management
  • Geo-Spatial applications
  • Impact Analysis
  • Master Data Management
  • Network Management
  • Product Line Management
  • Recommendation Engines

The more generic answer would be that graph databases can be a great fit for problems handling highly connected data.

The examples above are clear cases of use cases involving highly connected data , but as of now I’m not aware of any social networks, network management, or large scale recommendation engines built on top of one of the existing graph databases.

Original title and link: What types of applications might a graph database be well suited for? (NoSQL database©myNoSQL)


Neo4j 1.6 GA Release: Heroku, Cypher, Lucene 3.5

Announced last week, Jörn Kniv aka Neo4j 1.6 features:

  • Improved Cypher (the query language)
  • Web admin - Full Neo4j Shell commands, including versioned Cypher syntax.
  • Kernel improvements
  • Upgraded Lucene version to 3.5.

Also the Neo guys have been pushing quite a bit their public beta Heroku add-on.

Original title and link: Neo4j 1.6 GA Release: Heroku, Cypher, Lucene 3.5 (NoSQL database©myNoSQL)


Neo4j on Heroku: Building a Movie Recommendation Website for $0.00

Recently Max de Marzi has published sort of a getting started with Neo4j on Heroku guide. Here is how Max described it:

It takes a lot less effort to build a website these days than it used to. All it takes is a clever dwarf standing on the shoulders of the right giants. In a series of blog posts, I walk you through creating a movie recommendation website using Neo4j, Heroku, themoviedb.org, Processing.js, GroupLens, Marko Rodriguez and Michael Aufreiter. Free database, free hosting, free movie posters, free visualization, free dataset, free recommendation algorithm, just need to add a little code to bring them all together and BYOP (bring your own popcorn).

This will not get you a Netflix or Amazon like recommendation engine, but using a similar approach could definitely tell if Muhammad Ali is truly the greatest.

Original title and link: Neo4j on Heroku: Building a Movie Recommendation Website for $0.00 (NoSQL database©myNoSQL)


Friend Recommendations Using Gremlin With Neography

Max De Marzi:

Gremlin is a domain specific language for traversing property graphs. Neo4j is one of the databases that can speak the gremlin language, and as promised I’ll show you how you can use it to implement friend recommendations as well as degrees of separation.

Original title and link: Friend Recommendations Using Gremlin With Neography (NoSQL database©myNoSQL)

via: http://maxdemarzi.com/2012/01/06/gremlin-with-neography/


Getting Started With Ruby and Neo4j Using Neography

Getting started with Ruby and Neo4j is very easy. Follow these steps and you’ll be up and running in no time.First we install the neography […]

The traversal API looks really nice and comes in two flavors: the Neo4j REST API and a Ruby-esque one.

Original title and link: Getting Started With Ruby and Neo4j Using Neography (NoSQL database©myNoSQL)

via: http://maxdemarzi.com/2012/01/04/getting-started-with-ruby-and-neo4j/


Grails 2.0 and NoSQL

Graeme Rocher:

Grails 2.0 is the first release of Grails that truly abstracts the GORM layer so that new implementations of GORM can be used. […] The MongoDB plugin is at final release candidate stage and is based on the excellent Spring Data MongoDB project which is also available in RC form. […] Grails users can look forward to more exciting NoSQL announcements in 2012 with upcoming  future releases of GORM for Neo4j, Amazon SimpleDB and Cassandra in the works.

This is great news.

The very very big news would be a Grails version that doesn’t default anymore to using Hibernate for accessing a relational database.

Original title and link: Grails 2.0 and NoSQL (NoSQL database©myNoSQL)

via: http://blog.springsource.org/2011/12/15/grails-2-0-released/