December 2011 Summaries

Spring Data Neo4j is used for domain modeling, allowing developers to map entities and relationships into Neo4j nodes and connections. A Person entity is commonly used in applications and can be annotated with necessary Spring Data Neo4j annotations to interact with the database. The use of a repository enables retrieval of instances from the database, while a controller exposes the data to the web. The standard class diagram provides a visual representation of the domain model, making it easier for developers to understand and implement.

Google Groups and various Neo4j communities have been actively sharing news, updates, and resources related to the graph database. Heroku released a web version of their December newsletter featuring a @neo4j tutorial and an @urbandictionary case study. The OpenShift community also discussed using graphs on the cloud, with a blog post and screencast coming soon. TinkerPop celebrated its new release of the open-source graph stack #graphdb #nosql. Neo4j.rb 1.3.1 was released, along with several updates to the project, including the creation of a Ruby DSL for Cypher. A new version of Neo4jPHP 0.0.6-beta was also released, featuring fulltext indexing and named Cypher/Gremlin parameters. The Neo4j-Python community shared updates on neo4django, PynIT, and py2neo, with several new releases and demos. Spring Data Neo4j introduced an intro webinar and showcased its capabilities through a video on YouTube. Vaadin shared a sample project demonstrating the integration of Neo4j with their framework. The community also discussed various educational resources, upcoming events, conferences, and job opportunities related to Neo4j and graph databases.

Heroku has released a Neo4j-Graph Database Add-On, making it available to all registered beta-testers of the Heroku PAAS platform. This add-on allows users to store and query interconnected data using a graph database, which is well-suited for object networks with dynamic domains. The add-on provides hosted Neo4j servers, with generous amounts of RAM, and can be easily added to applications using the `heroku addons:add neo4j:test` command. Users can access their Neo4j instance via a REST URL or the Neo4j Web Administration UI, and can manage their graph database using various features such as node properties, relationships, and backups. The add-on is currently available for free with the test plan, and users can start exploring larger graphs right away.

Cypher, a query language for Neo4j's graph database, has been gaining popularity among developers and DBAs alike. A recovering SQL DBA shares their experience of transitioning to Cypher, highlighting the benefits of this new language, including its ability to scale horizontally with ease, handle large amounts of data efficiently, and provide real-time analytics capabilities. The author also discusses the challenges they faced while making the switch, such as adapting to a new paradigm shift from relational to graph-based querying. Overall, the post offers a unique perspective on the advantages and difficulties of working with Cypher.

The author of the text created a screencast that demonstrates how to set up a Neo4j instance via Heroku and connect to it from within a Google Spreadsheet using appscript. The process involves registering at Heroku, installing the heroku gem, creating and installing a Heroku app, adding a Neo4j addon instance, uploading existing Twitter data to the graph, creating a custom Ruby app, executing Cypher queries, connecting to the app using a Google Spreadsheet, and building a small bar chart from a Cypher query. The author notes that while the screencast is not perfect, it is an acceptable first attempt and encourages viewers to suggest topics for future screencasts or create their own screencasts about Neo4j topics.