GraphAware Blog - GraphAware

Organisations face a dilemma: the data they have gathered bears immense potential, yet leveraging it is a significant challenge. This blog post outlines an approach to solving this problem by combining graph technology with data orchestration.

A couple of days ago, we hosted a Logistics Optimisation webinar. We covered some challenges of Logistics Chains and talked about how graphs, graph technology, and Hume can help you tackle them.

Last week we at GraphAware hosted yet another webinar. This time we talked about Money Laundering and how Hume can help you detect money laundering activities. Don’t worry if you missed it; here is your summary of what we covered.

It is always a valuable opportunity to understand our product better and recognize user needs. At GraphAware, building Hume, a graph-powered insight engine, we are proud of making an impact on our customers’ success. However, we use Hume also to support our processes and help our own needs. In the case of the event that took place throughout December, we were also able to have great fun and integrate the team.

Last week, I had the pleasure of hosting a webinar with our Director of Product, Esther Bergmark, and our CTO, Christophe Willemsen. This webinar introduced our new release Hume 2.11, so we covered the most exciting features of the release, including no-code graph navigation, custom visibility of Actions in Perspectives, and Perspective API. The 2.11 version comes with more updates and advancements such as Configuration as Code and ​​Polygons in Geospatial Analysis - about which you can read in our release blog.

We are proud to announce the 2.11 release of Hume. Advanced Expand is introduced to Hume with this release, which lets users create complex queries to navigate the graph without using Cypher. Additionally, the visibility of Actions can now be defined per Perspectives, enabling a tailored exploration experience; a GraphQL API exposes data from Perspectives so that other apps can leverage the power of Hume. And finally, Configuration-as-Code allows administrators to manage Hume configuration files in a repository.

I like to think of 2021 as the year of consolidation for GraphAware. The growth, changes, hits and misses all somehow began to pull together the threads that have existed or developed through the last 8 years into one strong, coherent strand.

We are proud to announce the 2.10 release of Hume. With this release, Comments are introduced to Hume, which lets you add text, images, and links as comments to nodes and relationships. Additionally, Snapshots can now be shared, and Temporary Visualisations can be created and accessed by other users via a URL.

GraphAware is now going through an extremely exciting phase. In 2020, we launched our own amazing product Hume, the only graph-powered insights engine in the world, which helps companies shed light on their complex data and make smart decisions. Since then, we have been rapidly growing in all aspects. Our ambitious plans will need plenty of talented people, who want to have a direct impact on a company’s success. Right now, we are already advertising for multiple vacancies, and the number will only grow in the coming months (check out our career page if you are already intrigued).

GraphAware is proud to announce the 2.9 release of Hume. With this release, Alerts are available in Hume, a feature that greatly simplifies the daily work of analysts, data scientists, investigators, and data-savvy business users. And there is more:

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:

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:

GraphAware is proud to announce the release of Hume 2.6. This new release brings some major updates and exciting new features to our customers. In particular:

Few years ago I met Michal Bachman and some other GraphAware heroes at GraphConnect in San Francisco. In those days I also had my job interview for the company. Surprisingly, for the first time since I started my journey in IT, I didn’t find myself explaining how I could be useful despite not having a strong background in engineering and software development. On the contrary, Michal was interested in all the things I could do because of my non-traditional curriculum, with a PhD in Cultural Anthropology, some experience in JavaScript graph visualisation, and a genuine passion for networks and graphs....

GraphAware Hume helps governments in keeping their countries safe. In this 15-minute video, we demonstrate the use of Hume for contact tracing and smart quarantine in the context of the current coronavirus pandemic. Specifically, we will see how Hume can identify people at risk using actual and potential contact tracing, suggest who should be informed or quarantined, visually explain why someone is at risk, find quarantine offenders, and much more.

You’ve probably seen us already at Amsterdam, Stockholm, Madrid and London.

It’s been a year since I published the Graph Technology Landscape 2019 post on GraphAware’s blog. I consider this a success story because it got a lot of attention and publicity. The landscape was mentioned many times at different places; it was used by Emil Eifrem in his GraphTour and GraphConnect opening keynotes, it was displayed in conference halls, and I received many, many useful comments and feedback. I was even invited to Rik van Bruggen Graphistania Podcast to talk about it, and the episode was referred to in the Top 5 Neo4j Podcasts of 2019 blog posts as well....

BOSTON, July 23, 2019 /PRNewswire/ – GraphAware, a leading Neo4j ISV and consulting practice, today announced the official launch of its Italian Research and Development entity Graph Aware S.r.l., headquartered in Lecce, Italy.This strategic investment by GraphAware represents a significant expansion as an ISV, with a fast growing development team of thought-leaders in GraphDBs with Neo4j, Natural Language Processing (NLP), Machine Learning (ML) and Artificial Intelligence (AI).Led by Chief Scientist Alessandro Negro and CTO Christophe Willemsen,the Lecce R&D center is the main lab and development center for GraphAware’s flagship software platform Hume- with a dedicated local and remote development team...

Few years ago I decided that one day I would create a Graph Technology Landscape map, which would be useful for everyone who wants to discover the players around graph technologies. I started to collect the companies and products, but my research has never manifested into a proper blog post. Till now. I am happy to announce, that the first version of my landscape is published, I hope we can consider this as a start of a long journey.

2018- it’s been such a whirlwind of activity at GraphAware, and we’re so proud of everything we’ve accomplished this year.In fact, we grew and grew, announcing ourselves in Australia and then, later in the year, expanding into the Americas.“Neo4j is one of the most disruptive and transformative technologies I have seen in my career,” said Kyle McNamara, CEO, Americas. His team are well on their way to increasing GraphAware’s presence and strengthening the already close bond we have with Neo4j.

BOSTON, MA, Nov. 28th, 2018 – GraphAware, a leading Neo4j consulting practice, today announced the official launch of its US entity GraphAware, Inc., headquartered in Boston, MA. This strategic investment by GraphAware aligns with Neo4j’s own rapid market expansion.

Nearly six years ago I started reading about this thing called Graph Data. Now unlike almost everyone in the modern world of Graph, I am not a coder. I was once upon a time but it has been many years since I typed a line of code. No I do not have a GitHub login. As an enterprise architect I often joke that I do powerpoint for a living. But I could see how this re-envisioning of data and how it could be used would transform enterprises. It is not just a technical change. It changes everything. People. Organisation. Knowledge....

What a year it’s been for all of us at GraphAware!

Last month, the 5th edition of GraphConnect San Francisco took place at the Hyatt Regency SF. It was the biggest graph technology event ever and GraphAware proudly contributed as a sponsor, with one main talk, two lightning talks and our GraphHero stand ｡^‿^｡ This edition’s big announcement was the upcoming new landmark release of Neo4j 3.1, “The database for the connected enterprise”, which introduces a new state-of-the-art clustering architecture and new security architecture to meet enterprise requirements for scale and security. There will be a lot to say about this release, but you can already try the beta release as...

A great part of the world’s knowledge is stored using text in natural language, but using it in an effective way isstill a major challenge. Natural Language Processing (NLP) techniques provide the basis for harnessing this huge amountof data and converting it into a useful source of knowledge for further processing.

For most organisations, data security is extremely important. The topic comes up every single time we are training, consulting,or otherwise engaging in the world of graphs and Neo4j. At the same time, security is very difficult and time-consuming to get rightand the implications of getting it wrong can be serious. In this blog post, we introduce the integration of Spring Securityinto Neo4j which provides important security controls and mechanisms for enterprises and governments that make use of theworld’s most popular graph database.

At GraphAware, we help organisations in a wide range of verticals solve problems with graphs.Once we come across a requirement or use case two or three different times, we typically create an open-source Neo4j extensionthat addresses it. The latest addition to our product portfolio, introduced in this post, is a simple library that automaticallyexpires data from the Neo4j graph database.

GraphAware is very proud to sponsor GraphConnect Europe 2015, the only conference thatfocuses on the rapidly growing world of graph databases and applications that make sense of connected data. The conferencetakes place in London on 7th May 2015.

Graph Aware Ltd. is excited to announce their new partnership with Glasses Inc. Managing Director Michal Bachman claimsthat wearers of GA-Glass become truly graph aware, allowing them to boldly go where no Glass has traversed before.

Specialist in Neo4j consultancy, training, and software development, Graph Aware Ltd has been selected as one of NeoTechnology’s first UK solution partners, under its newly launched partnership program.

In this post, we’d like to introduce the first version of the GraphAware Neo4j ChangeFeed - a GraphAware Runtime Modulethat keeps track of changes made to the graph.

Modelling and querying time-based events in a graph is a fairly common discussion topic and a frequently asked questionon Q/A sites. In this blog post, we evaluate some of the common approaches and introduce GraphAware TimeTree, a GraphAware Framework Module that simplifies modelling time and events in Neo4j.

In the first part of this short series aboutrandom graph models, we talked about why they are useful and had a brief look at two of them: Erdos-Renyi graphs andBarabasi-Albert model. In this post, we take a look at the “small world” phenomenon and another network model, namelythe Watts-Strogatz model.

Efficient counting of relationships in Neo4j was the cornerstone of my Master Thesisand the reason the very first GraphAware Frameworkmodule called the Relationship Count Module was born. The improvements in Neo4j 2.1around dense nodes and the addition of getDegree(…) methods on the Node interface made me eager to do some benchmarking around relationship counts again.

When one obtains a graph data from a measurement on a real world network, it is sometimes useful to make comparison witha random graph. Such graph is characterised by certain degree distribution, which you can imagine to be a list of degreesof nodes present in the network. The most interesting distributions have certain functional dependence which allowsone to infer what processes are dominant in formation of the network. The processes consequently characterise therelationships between the nodes.

One of the main goals of the GraphAware Framework is to simplify andspeed up development with Neo4j. Although it is called a “framework” for reasons explained elsewhere, today we willsimply treat it as a library of useful, tested, and documented Java code. The feature we will introduce is calledImproved Transaction Event API, which is exactly what it says on the tin.

A couple of days ago, I wrote about unit testing with GraphUnit.GraphUnit tested the state of an embedded Neo4j database. What if you run Neo4j in standalone server mode?Fortunately, you can still test it and match subgraphs using the GraphAware Neo4j RestTest library.

Testing the state of an Embedded Neo4j database is now much easier if you use GraphUnit, a component of the GraphAware Neo4j Framework.

Today, it is exactly one year ago since Graph Aware Limited was incorporated. It started as a one man show, whilst I was finishing my MSc. Thesis at Imperial College London. Since then, we’ve been growing slowly but steadily and will be moving to our new London office fairly soon (announcements to come). We have happy clients in London, New York, Copenhagen, Barcelona, Prague, and Accra.

Recently, we announced the GraphAware Framework. Today, I would like to introduce its first feature called GraphUnit. GraphUnit is a component that helps Java developers unit test their code that talks to Neo4j and mutates data.

In this short blog post, I would like to introduce the GraphAware Neo4j Framework.Its goal is very ambitious: we’d like to make it as useful for Neo4j developers, as the Spring Framework is for Java developers. The Framework aims at speeding up development with Neo4j by providing a platform for building useful generic aswell as domain-specific functionality, analytical capabilities, graph algorithms, and more.