August 2012 Summaries

The Neo4j company recently hosted a Cypher webinar that covered various topics related to their graph database management system. The discussion addressed questions from attendees regarding data migration, performance optimization, and the use of machine learning algorithms within Cypher. Additionally, the presentation touched upon the implementation of Cypher in other programming languages and future plans for backwards compatibility in upcoming versions. The attendees' feedback was overwhelmingly positive, with many praising the intuitive nature of Cypher and its ability to express "what" one wants to retrieve from a graph without specifying how. The webinar concluded with a thank you message from Andreas Kollegger, highlighting the importance of community engagement and user feedback in shaping the future of Neo4j.

We chose a dataset that was easy to understand and interesting enough for attendees of the conference, which is why we selected only the NOSQL NOW conference program from that day. Conference data is well-connected and has opportunities for challenging data model discussions and insightful queries. We set up a Heroku instance connected to a provisioned Neo4j database hosting an informational website about Neo4j. A small ruby script with the neography gem populated the database, allowing attendees to download the graph.db directory for their local Neo4j server. Andreas ran a successful session working with the NOSQL NOW conference dataset, introducing Neo4j and Cypher in his presentation "Introduction to Graph Databases".

The Silicon Valley Java User Group hosted a meetup at Google HQ in Mountain View, sponsored by GraphConnect. The event drew around 200 attendees who discussed REST APIs. Attendees enjoyed free food and drinks, including pizza, beer, and cookies, as well as free GraphConnect t-shirts. Arvid Kumar was awarded a free pass to GraphConnect for winning the meetup.

The author attended JRubyConf.EU, a conference where they sponsored, spoke, and participated in the "Track & Hack" project. The project used RFID tags to create an interaction graph of attendees, which was visualized on a big screen for everyone to see. The author gave talks about Neo4j and its integration with Ruby, and had discussions about graph-related topics throughout the conference. The author also showcased their own local RFID-Graph hosted on Heroku, allowing attendees to play around with it in real-time. The event was well-received, with many people showing interest in Neo4j and the tracking technology used in the project.

Neo4j's High Availability feature allows for the replication of graph data across multiple synchronized servers, enabling high availability and data redundancy regardless of whether they are located in a single data center or distributed globally. This ensures that data can be accessed by clients even if one server becomes unavailable, while also addressing concerns about data crossing public networks, which can be mitigated using Virtual Private Networks (VPNs).

We're excited to announce that the meta-data from our Usage Data Collector (UDC) is now publicly available, while maintaining sensitivity for privacy concerns. This move aims to make the data useful for everyone in the community. Additionally, we've introduced a new feature called `CREATE UNIQUE`, which allows users to uniquely create patterns of data in their graphs. The latest version of Neo4j, 1.8.M07, includes several notable changes, such as improved kernel compatibility, console disablement, and edition information for different types of licenses. Users can now download the latest version immediately from Neo4j.org or discuss it on the community forums.

To test a fully assembled system, a database must be properly integrated into the set-up and tear-down of the test environment. This is particularly advantageous for JVM-friendly developers using Neo4j, as the database can be instantiated directly in code. However, setting it up requires some work. NoSQLUnit simplifies this process by providing support for bootstrapping a Neo4j server into unit testing, making it easier to get started.

Neo4j has expanded its Meetup graph with new additions, now boasting 27 groups worldwide and over 2500 members in 24 cities. These meetups provide a platform for individuals to join the graph community and receive support from the Neo team. In anticipation of GraphConnect conference in San Francisco, free tickets will be given away to participating meetups until the end of October. Additionally, the Community Team is offering assistance to help anyone start their own Graphdb meetup.

Last week's Graphs in the Bay Area meetup saw around 50 attendees, sponsored by GraphConnect and QCon SF, with a small keg of local beer, pizza, and free conference tickets provided. Three local presenters showcased their projects, including Mathieu Bastian on graph database use cases, Alexander Smirnoff on his Neo4j JCA connector and start-up Netoprise, and Corey Farwell on his RIAARadar app built on the Neo4j graph database. The lucky winner of conference passes announced was Jason McVetta, a consultant at Harvard Medical School who keeps up-to-date with various databases and tools. An upcoming SF Graphdb Meetup is planned, again sponsored by GraphConnect, promising to be "pretty sweet".

The text discusses the basics and features of Spring Data Neo4j, a graph database framework that allows developers to work with connected data. It answers common questions about how to use the framework, including how to start traversals from any node, explore graph databases using tools like Toad and Navicat, and optimize queries for better performance. The text also provides information on data storage, high availability, and clustering, as well as its compatibility with other Spring frameworks and technologies. Overall, it aims to provide a comprehensive overview of the framework's capabilities and limitations, making it easier for developers to get started with using Spring Data Neo4j in their projects.

Spring Data Neo4j is a reflection of a graph's nature, allowing it to work well with other systems while making sense of connected data. It demonstrates that graphs are everywhere and provides tools for exploring graph databases like Toad and Navicat. The database stores data in custom storage formats optimized for nodes, relationships, and different property types. Neo4j Enterprise supports fail-over and load-balancing in a cluster with high availability, where each node runs on its own machine and filesystem using a custom protocol for syncing. The Spring Data Neo4j add-on is currently in development, but there are plans to make it work in a JEE environment via CDI. Indexing fields can be beneficial, but it depends on usage patterns and queries, and there are tools available for one-time data setup and performance optimization.