With today’s blog, we will dive a little bit into front-end application development. When creating complex applications, as we do in GraphAware, we need to handle large and complicated application states to present our users with correct user interfaces. Making application state predictable and explainable is one of the key challenges for the successful agile frontend development team. As we often like to point out, graphs are proving to be a successful solution to many existing problems. So, could we learn from graphs to handle application state in a more predictable manner?
Knowledge sharing has always been extremely important for Engineering at GraphAware.Whether it is techniques, tools or technology, lessons learned from our consulting engagements, or experience in general,sharing sparks conversation, creativity and discovery of different or better ways to do things.
Only a few things are more satisfying for a graph data scientist than playing with Neo4j Graph Data Science library algorithms, most probably running them in production and at scale. Possibly also using them to fight against scammers and fraudsters that every day threatens your business.
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.
“Alright, could you please tell us a few benefits and drawbacks of working with microservices?” - starts the usual tech interview question, and the traditional answer often follows: “They’re smaller; therefore, they’re easier to develop and to troubleshoot. There’s better scaling control on parts of the system. They can be written in different programming languages. They can be deployed individually.”
“Alright, could you please tell us a few benefits and drawbacks of working with microservices?” - starts the usual tech interview question, and the traditional answer often follows: “They’re smaller; therefore, they’re easier to develop and to troubleshoot. There’s better scaling control on parts of the system. They can be written in different programming languages. They can be deployed individually.”
So, you’ve built an amazing application with your favorite framework such as Vue.js or React.js and now it’s time to build a Docker image and ship it.
Neo4j Desktop, part of the Neo4j Graph Platform, is a client application that installs on your desktop OS. It lets you get started quickly by downloading and installing the enterprise edition, and supported plugins. You can group related graphs and applications under a Project. You can also build single-page web applications that run within Neo4j Desktop and have access to these services provided by Neo4j Desktop. There are a number of apps available at https://install.graphapp.io/
When developing web applications with frameworks like Vue.js the best approach is to subdivide it into well-defined and reusable components for the user interface, with the business logic being encapsulated in ‘services’.
