![]() It is necessary to build queries already focused on the current use of the database. “ For now there is no way to visualize what we have in total within the Database. “How do I get all the nodes I created for which I’ll never remember the single ids?” I started a few simple queries, then I asked my self: The query language is good, the documentation is good, there are also a few clients in different languages and I was happy to also find a Typescript ORM for it.Īs I finished studying it, and set it up and running, I have seen their UI to manage the graph, Ratel. What kind of queries would you run, which could utilize the weights? Would you use these as filters? Or, as a way to sort the nodes at the end of the edge?”īut ok, now the problem is fixed, everything should be fine now, let’s skip it. But, hadn’t come across a good use case to warrant it. That’s been on my mind for a while, as something we should implement. “ We don’t have a way to attach weights to edges. In a Github issue of 2017 ( ), someone asks if it is possible to add edge attributes like in all the other graph databases. In a graph you, frankly, want the edge attributes. During my study, I also verified a few of the things I was interested on. ![]() I always want to have the big picture of the tool I use, hence I studied it from scratch to the end. Encouraged by their own description of themselves, I started studying it then. ARANGODB VS NEO4J FULLWorking with javascript full stack, it seemed a great choice. I encountered DGraph, suggested by the fact that it allowed to use GraphQL. ARANGODB VS NEO4J HOW TOI am not a graph database expert, neither a database expert in general, but for my projects I need to know how to use them.īased on my needs, I skipped a few databases like Neo4J and MongoDB. This common feeling led to the rise of graph databases starting from Neo4J and going with the latest ones, among which Amazon Neptune ( Graph Database as a Service) launched in 2017, ArangoDB and many others. When it comes to develop a graph oriented system like a social network, or an analytics system or anything in which the structure is essentially a graph, you feel uncomfortable on working with the good, old SQL. ![]() My short experience with DGraph as of Jan 2020 ![]()
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