GraphAware Blog

Say you have a graph-based project in mind. Be it research in life sciences, a fraud detection machine, or possibly a recommendation app. Anything that relies heavily on relationships between data points is a good case for a graph.

It has been over 8 years since I’ve written the first lines of code for the GraphAware Neo4j Framework as part of my MSc. thesis. That’s when the name GraphAware, as well as the (then) one-man show Neo4j consulting company was born. It is therefore my bittersweet duty to take you on a small trip down the memory laneand announce that we have decided to discontinue the development and support of the Framework and all of its modules.

GraphAware is proud to announce the 2.8 release of Hume, our graph-powered insights engine. The release adds further unique capabilities to Hume’s knowledge graph visualisation and graph data analysis capabilities. Analysts, data scientists, investigators, and data-savvy business users will profit from these benefits:

CDC (Change Data Capture) is a well defined software design pattern for a system that monitors and captures data changes so that other software can respond to those events.

Phonetic matching attempts to match words by pronunciation instead of spelling. Words are typically misspelled and exact matches result in them not being found.Algorithms such as Soundex and Metaphone were developed to address this problem and they have found usage in the areas of voice assistants, search, record linking and fraud detection, misspelled names of things (for example, medical records) etc.

GraphAware is proud to announce the 2.7 release of Hume, our graph-powered insights engine. The release significantly enhances Hume’s knowledge graph visualisation and graph data analysis capabilities. Analysts, data scientists, investigators, and data-savvy business users immediately get the following main benefits:

Enterprise Integration has existed since many, many years. Although it might seem like an old set of patterns, the reality is that more and more data silos, protocols and systems have been created in recent times which increase the need for the capabilities of an Enterprise Integration platform.

The release of Neo4j 4.0 brought many improvements, one of them being areactive architecture across the stack, from query execution to clientdrivers. But how does that compare to other approaches ? As stated inthe reactive manifesto, areactive system is more scalable and responsive, by having a more efficient resource usage.

In our last Metropolitan Art Collections post we ingested and processed part of a dataset containing more than 470,000 artworks from The Metropolitan Museum of Art and created a knowledge graph using Hume, GraphAware’s insights engine.

The Metropolitan Museum of Art recently published a dataset of more than 470,000 works of art under the CC-zero License. Representing such a collection as a knowledge graph allows us to explore it in a unique way - seeing the artworks, their authors, donors, mediums, tags, or art movements deeply connected, being able to traverse the links between them and discover unexpected relations.