Photo credit When text-to-query approaches (specifically, text2cypher) first entered the scene, I was a bit uncertain how it was useful, especially when existing models were hit-or-miss on result accuracy. It would be hard to justify the benefits over a human expert in the domain and query language. However, as technologies have evolved over the last couple of years, I’ve started to see how a text-to-query approach adds flexibility to rigid applications that could previously only answer a set of pre-defined questions with limited parameters.

Photo credit After working on a new online Spring Data Neo4j course, I learned a couple more things about updating an entity. The course required a different set of scenarios than outlined in my previous SDN update blog post, so I wanted to cover those scenarios, as well. Spring save() method First up is the out-of-the-box save() method that is provided by Spring as a default. This method takes an input of the entity object you want to save to the database.

Photo credit You may have heard quite a bit of buzz around reactive programming or reactive principles in recent months or years. Some people say it is the future, while others prefer their existing monoliths. So what is all the fuss actually about? What is reactive? Is it beneficial? As with all things in life, it depends. :) Remember, that technical decisions are often large investments of time - resources to create it and/or maintain for lengths of time.

Photo credit Our previous post (Part 1) on this topic introduced us to Spring Data Neo4j and showed the architectural differences between version 5 and the latest version 6. This post begins the migration process by taking a Spring Data Neo4j 5 application with OGM and upgrades to the dependencies and syntax changes of Spring Data Neo4j 6. Without further ado, let’s dive in! Current application overview The code for today’s migration is a specific branch in the migration Github repository.

Photo credit A major upgrade to Spring Data Neo4j was released at the end of last year as part of the Spring Data release train. If you were involved in Spring Data and Neo4j news before that, you may have seen hints of this coming with the SDN/RX library entering the scene in late 2019. The library brought with it a lighter footprint, as well as a more straightforward implementation of features to reduce confusion and errors (therefore also improving efficiency) in development and production.

Photo credit I have had a couple of Github projects demonstrating bits of functionality for Spring Data Neo4j, but they had last been updated in 2020 when the new Spring Data Neo4j 6 was still a beta version known as SDN/RX. Since there have been several changes since then, I thought I would give the projects a refresh and make them current. Project code: SDN Marvel (imperative) SDN(rx) Marvel (reactive)