February 2017 Summaries

The Neo4j Movies Template is a demo application built using Flask and React.js, showcasing how to build a web app with Neo4j as the graph database. The template includes a classic movie database with nodes for Movie, Person, Genre, and Keyword, connected by relationships. Users can add ratings to movies and view their previous ratings on their user profile or the movie detail page. The application uses the Bolt driver for Neo4j and provides an API documentation. The code is written in Python and includes a detailed explanation of how to use the Bolt driver, serialize data, and implement common features such as authentication, registration, and rating movies.

In a recent move, we're sharing insights from UK-based research firm Bloor Research on Neo4j graph database, providing an in-depth analysis of its strengths, weaknesses, and use cases within the broader database ecosystem.

Neo4j is publishing a more focused update once a week instead of covering everything that happened in the month, with an email address [email protected] for feedback. Andrew Bowman, also known as InverseFalcon, has been answering 79 questions on StackOverflow and is active on the Neo4j Discord channel. The next online meetup will feature Jesús Barrasa talking about his experiences in the RDF and graph worlds. A new Neo4j Sandbox allows users to play around with Neo4j quickly, while a recent Forbes article highlights NASA's use of Neo4j to connect related topics. Community experiments include a Chrome bookmarklet for charts and sorting/searching/paging tabular results in the Neo4j Browser, as well as blog posts on loading CSV and JSON data into Neo4j. Optimizing Neo4j queries involves tips from the field team, while the Graphistania podcast continues to interview Neo4j community members. Learning resources include intro tutorials for Neo4j with Java and JavaScript drivers.

Grant Duncan Grant first became familiar with Neo4j when he started working for Cambridge Intelligence, where he found the tool's documentation and Cypher query language extremely user-friendly. He has since been involved in several projects using the database, including a company mapping project that utilizes Neo4j to determine where certain failures within large conglomerates originate, as well as a project analyzing online world trade network data to identify relationships between countries' biggest trade partners. Grant recommends the online Neo4j development course for those looking to learn more about the platform and praises its ease of use, even for those without prior experience with graph databases. He also notes that Neo4j is a great tool for working with Cambridge's network visualization tool KeyLines, and encourages others to share their own Neo4j projects in future 5-Minute Interviews.

Theo is a Swift framework that provides full support for Neo4j, a graph database. It offers features such as CRUD operations for nodes and relationships, Cypher support, transaction support, and better integration with popular package managers like CocoaPods, Carthage, and the Swift Package Manager. Theo can be easily integrated into existing iOS or macOS projects as a git submodule, via Cocoapods, Carthage, or the Swift Package Manager, regardless of whether the app is written in Objective-C or Swift. The framework has been available since Swift 1.2 and plans to stay on top of the latest Swift versions. Theo interfaces with Neo4j via the REST API but also supports the newer Bolt protocol, which is a priority on its roadmap. The framework allows developers to create nodes, fetch nodes, execute Cypher queries, run transactions, and perform other operations on the graph database. An example project demonstrates how to use Theo in an iOS project, showcasing its ease of integration and usage.

While albumprinter relies on a polyglot persistence architecture to manage and create products from personal photo collections, they use Neo4j to provide a way for customers to easily organize and sort their photos. The company chose Neo4j due to its ability to create relationships between photos based on metadata stored in the database. This graph database provides advantages of both NoSQL and relational databases, including reliability and scalability. Albumprinter has found that using a polyglot persistence architecture with multiple databases can help improve scalability and data backup capabilities. However, they have had to adapt their approach to normalization and data modeling, as traditional relational models do not apply in the same way in a graph database. Despite some challenges, albumprinter is happy with their choice of Neo4j and has been able to create features quickly, thanks to its power.

We are developing a graph recommendation system for Part-Up, an online platform that enables people to create and manage virtual teams. We need to serve users one team that perfectly matches their interests, ambitions, and moods from over 400 available public teams. To achieve this, we are using collaborative filtering with a hybrid database structure, combining MongoDB and Neo4j. Our system architecture includes GraphAware for recommendation framework, Java Importer for data import, and JCypher for Neo4j interaction. We have designed algorithms to overcome filtering challenges such as data sparsity, grey sheep, scalability, shilling attacks, and synonymy. Our approach is item-based collaborative filtering with adjusted cosine similarity and weighted sum, allowing us to provide personalized recommendations to users. The system is domain-independent, easy to customize, scalable, and transparent, making it a necessity for any platform offering team management services.

The Neo4j community has been actively contributing to various projects, including articles and blog posts showcasing different use cases and features of the graph database. Some notable examples include a post by Max de Marzi on extending security features in Neo4j 3.1 and another by Brian Roy analyzing the accuracy of images classified by the AWS Rekognition API using Neo4j. Graph visualization tools like Tom Sawyer Perspectives have also been updated, with version 7.6 introducing support for maps to display location-based information. Additionally, new libraries and drivers were released, including py2neo version 4.0.0b2 and neo4j_sips version 0.2.16. The community has also been exploring the potential of Neo4j in various domains, such as geospatial features, sports analytics, and climate change discussions.

Swain, from Right Relevance, uses Neo4j to analyze social media conversations and monitor public sentiment on important issues such as Brexit and the US Presidential election. He initially chose Neo4j due to its ease of use and found it extremely useful for developing graph-based projects. Swain has worked with Neo4j since version 3.0, which introduced support for whole-graph algorithms like PageRank and machine learning for community detection. The company used Neo4j to analyze social media conversations around the US presidential election, scaling their cluster and receiving technical support from Neo4j's Developer Relations team. Swain believes that if he were to start over with Neo4j, he would spend more time on analysis and less time writing graphs, given his background in SQL data modeling. Overall, Swain has had a positive experience with Neo4j, citing the company's technical support as particularly excellent.

The Neo4j community has expressed difficulties in attending meetups due to location or time constraints, prompting the Developer Relations Team to revive the Neo4j Online Meetup. The team will organize regular online events, including talks, trainings, and hands-on workshops, which will be streamed on YouTube Live and discussed on the Neo4j-Users Slack group. The first presentation by Michael Hunger is scheduled for February 15th at 17:00 UTC, featuring a demonstration of importing and querying Buzzfeed's TrumpWorld dataset using Neo4j and Cypher. The team invites community members to share their interests and suggestions for future events, as well as informal submissions for lightning talks or full presentations.

With Neo4j, Gallium Artistic Services uses graph databases to gather memories from players and provide insights, allowing them to interact with historical figures like Albert Einstein. The AI system, Proxi, is trained on these memories to understand connections between different concepts and emotions, creating a "social network of the mind." By analyzing these relationships, Proxi can offer valuable insights and opportunities for shared experiences among players. Graph databases provide an easy-to-analyze data structure that allows the company to harness complex memory patterns and create meaningful connections between seemingly disparate pieces of information.

The author developed an app called WikiBrowser Service to map relationships between Wikipedia entries, utilizing open-source technologies such as Java Spring and Pivotal Cloud Foundry. The tool allows users to navigate articles through both article links and Wikidata structural relationships, creating a concept map that can be used for learning and research purposes. The application consists of a single HTML 5 app along with microservices running in the cloud, which provide simplicity and location independence. It uses Neo4j graph database services and Bitly short URLs to facilitate data exchange between services. The tool offers several use cases, including breadth-first search, finding shortest paths, navigating to root, and degrees of separation. These features enable users to explore complex relationships and structures within Wikipedia entries, providing valuable insights for learning and research purposes.

Neo Technology's CEO shares their journey to Neo4j, a graph database that attracted them due to its ability to handle complex nested data and large-scale dependency graphs. They were involved in designing a data integration platform for Barclays Bank, where they worked on building an API for publishing standardized snapshot data and a streaming query processor. The company is now working to make Cypher, a declarative language for graph querying, into a living industry standard. With the support of various startups and established database vendors, Neo Technology aims to see graph technology grow and become more accessible, with Cypher becoming the "SQL of Graphs". A recent openCypher Implementers Meeting was organized to bring together companies and developer groups working on Cypher, with a focus on language evolution and multiple graph processing. The meeting is expected to lay the groundwork for a formal open standard language.