neo4j: All content tagged as neo4j in NoSQL databases and polyglot persistence
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 ( ©myNoSQL)
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 ( ©myNoSQL)
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? ( ©myNoSQL)
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 ( ©myNoSQL)
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 ( ©myNoSQL)