Likelihood to Recommend Like any NoSQL database, whether it's
MongoDB or not, it's best suited for unstructured data. It's also well suited for storing raw data before processing it and performing any type of ETL on the data.
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 Scalable Instantly and automatically serverless database for any large scale business. Quick access and response to data queries due to high speed in reading and writing data Create a powerful digital experience for your customers with real-time offers and agile access to DB with super-fast analysis and comparison for best recommendation 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 Expensive, so be careful of the use case. We had a thought time migrating from traditional DBs to Cosmos. Azure should provide a seamless platform for the migration of data from on-premises to cloud. 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 Likelihood to Renew It's efficient, easy to scale, and works. We do have to do a bit of administration, but less now than when we started with this a couple of years ago. Microsoft continues to improve its self-management capability.
Read full review Usability It has very good compatibility and adaptability with other APIs and developers can safely create new apps because it is compatible with various tools and can be easily managed and run under the cloud, and in terms of security, it is one of the best of its kind, which is very powerful and excellent.
Read full review [Based on] Query Language, Performance on small and large data sets, integration and deployment, analysis, API support, Interactive UI.
Read full review Support Rating Microsoft is the best when it comes to after-sales support. They have a well-structured training and knowledge base portal that anyone can use. They are usually quick to respond to cases and are on point for on-call support. I have no complaints from a support standpoint. Pretty happy with the support.
Read full review Alternatives Considered Cosmos DB is unique in the industry as a true multi-model, cloud-native database engine that comes with solutions for geo-redundancy, multi-master writes, (globally!) low latency, and cost-effective hosting built in . I've yet to see anything else that even comes close to the power that Cosmos DB packs into its solution. The simplicity and tooling support are nice bonus features as well.
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's made managing raw data much easier It provides a way to maintain raw data at a low cost It's easy to massage the data 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