Likelihood to Recommend Use cases provided by default are good and can be improve better using Machine Learning and AI. AQL query language is very simple and efficient in use if anyone using SQL can quickly learn AQL Language.
Developers can easily map the database and can access various patterns like search, ranking.
JSON and semantic search is the latest and next-generation technology to implement to access and extract large datasets.
Read full review Neo4J is great for creating network graphs or illustrating how things are related. It is also good for finding individuals or things that have greater influence than others in a system. It is not appropriate if you have standard data sets that can be analyzed using conventional methods or visualized using
Tableau , for example.
Read full review Pros AQL query language is big plus for ArangoDB It can be implemented cloud as well as on-prem Search Engine is a very good option for ArangoDB Read full review Mature Query language, I found Cypher QL to be mature in handling all sorts of problems we throw at it. Its expressive enough to be intuitive while providing rich features for various scenarios. Native support for REST API, that makes interacting with Neo4J intuitive and easy. Support for Procedures in Java, procedures are custom code that could be added to the Neo4J to write custom querying of data. The best part about the procedures is it could be invoked using the REST API. This allows us to overcome any shortcomings from their Cypher query language. Nice UI and interface for executing the Query and visualizing the response. UI access controlled by User credentials allows for neat access controls. Awesome free community edition for small-scale projects. Read full review Cons By providing the free services for few months will be help understand for beginners Enhancing features in dashboard and can make UI more user-friendly Should conduct more surveys and adv to improve scalability Read full review One of the hardest challenges that Neo4j had to solve was the horizontal scaling problem. I am not updated on recent developments, but at the time of my use, I couldn't find a viable solution. Neo4j does not play with other open source APIs like Blueprint. You have to use the native Neo4j API. There wasn't a visual tool to see your data. Of course, third party tools are always available, but I would have loved something which came with the Neo4j bundle. I love that Docker comes bundled with Kitematic, so it's not wrong to hope that Neo4j could also ship with some default visualization software. Read full review Usability [Based on] Query Language, Performance on small and large data sets, integration and deployment, analysis, API support, Interactive UI.
Read full review Alternatives Considered It uses AQL query Language, which is different from other Databases. It has flexibility to integrate in cloud, on-prem anywhere
Read full review Neo4j is a graph store and has different use cases compared to another NoSQL Document store like
MongoDB .
MongoDB is a bad choice when joins are common as existing operators for joining two documents (similar to tables in a relational store) as Mongo 3.5 use SQL like join algorithms which are expensive.
MongoDB is a great choice when distributed schemaless rich document structures are important requirements. Cross document transaction support is not native to
MongoDB yet, whereas Neo4J is ACID complaint with all its operations.
Read full review Return on Investment It is very powerful tool and should adv more to improve sales Should conduct more free trails and trainings Open source and runs everywhere Read full review Positive: Less complex queries on graph structures, than in relational databases. Negative: maintenance is a huge deal, things doesn't work and break, requiring lengthy restore operations. Read full review ScreenShots