Neo4j IDE and graph visualization tool

Cypher is Neo4j’s own open source declarative query language, designed to work similarly to SQL, but specifically for property graphs. A couple of key advantages of Cypher are its closeness to naturally spoken language and its utilization of pattern matching, both of which help make it intuitive to learn.

Cypher is also the language used by a number of our other supported databases such as Memgraph and Kuzu.

Getting started with Neo4j and gdotv is easy. It’s just one simple installation, available on Windows, macOS and Linux. No prerequisites, additional configuration or installation required. You can get started in seconds.

gdotv automatically detects your connection setting requirements based on your database hostname and prompts you for the required information for an easy onboarding experience.

Want a step-by-step walkthrough? Make sure to check out our demo, Get Started with Neo4j + gdotv on YouTube.

Neo4j supports the Cypher query language – the most widely adopted, fully-specified, and open query language for property graph databases. It provides an intuitive way to work with property graphs.

Cypher is a declarative query language specifically designed to handle querying graph data efficiently. With Cypher, you express what to retrieve but not how to retrieve it. This allows you to focus on the problem domain instead of worrying about the syntax.

Cypher was designed to be easy to learn but very powerful when it comes to graph analytics. This means that you can use Cypher to write complex queries relatively easily.

gdotv’s Cypher query editor provides syntax highlighting, autocomplete suggestions and built-in Cypher documentation to help you optimize your queries.

Graph databases typically fall into two models: Labeled Property Graph (LPG) and Resource Description Framework (RDF).

The LPG model covers a broad class of databases, including Neo4j, that use nodes, edges, properties and labels to represent graphs. They are optimised for real-time use and excel in applications like fraud detection, social network analysis and recommendation algorithms. There are also a wide range of methods to enforce schema compliance, with flexible conventions and definitions.

The RDF model refers to a highly standardized form of data management using global identifiers. Information is stored as a series of directed “triple” statements connecting a subject, predicate and object together. In addition, various languages built on RDF (such as RDFS and OWL) allow the construction of sophisticated ontologies and semantic reasoning. The high level of standardization also simplifies data integration from disparate sources. This makes RDF ideal for applications in large knowledge graph construction and research.

LPGs excel when performance and ease-of-use are a priority. Users typically find LPGs more intuitive, and they can be tailored to specific use-cases quickly and easily without the semantic complexity or steep learning curve of RDF.

Organizing data derived via powerful data visualization tools have several real-life applications. Graph visualization and analysis resources allow users to make informed decisions based on actual data. Here are a few examples of the type of companies or clients that can leverage Neo4j along with the robust data visualization aspect offered by gdotv:

• Data scientists and managers: Visual data analysis allows users to uncover and understand emerging patterns and relationships between data points, discover valuable insights to make informed decisions on ways to transform business processes.
• Cyber security groups: Build security graphs to represent protected assets, infrastructure, code dependencies or networks and visualize the connected relationships throughout the organization.
• Business intelligence analysts: Create customized reports and visualizations that can be easily executed for analysts to investigate and communicate on interaction between business data points.
• Fraud detection: Detect fraud patterns by modeling relationships between transactions and financial actors, then interactively visualize graph data to uncover and present potentially suspicious behavior.

gdotv Desktop runs locally on your device – no deployment needed and no handing over your data to a third-party system. Everything happens within your organisation’s network, and we have no access to your data.

Our Team and Enterprise versions run within your own environment, providing the same security benefits.

It’s easy to install and configure too: our setup wizard gets you connected to your graph database in seconds.

Yes! Whether you’d like to access multiple Neo4j instances, or interact with other graph vendors at the same time, gdotv doesn’t limit you to a single database. You can establish as many connections as you like from within our intuitive UI, and seamlessly switch between them.

Connecting is easy, and there’s no need to manage multiple vendor specific user interfaces. With gdotv, query and compare results from all your RDF and Labeled Property Graph databases under one umbrella.