Likelihood to Recommend 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 QuestDB is well suited for any use case where you need to store large amount of data and the performance is the key factor - for both reads and writes. So use cases like market data storage in financial industry, any kind of telemetry, etc.
Read full review Pros 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 Extreme performance. Super easy to use. Compatibility with Influx line protocol. PostgreSQL compatibility. Out of order timestamps. Support for multiple records with same timestamp. Integration with Grafana. Team responsiveness. Read full review Cons 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 New project so needs a bit polishing. 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 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 We were looking for time series database that will be able to handle L2 market data and came across QuestDB. From the beginning we were impressed how well the QuestDB performs and that it actually significantly outperforms all other open source TSDB on market like
InfluxDB ,
ClickHouse ,
Timescale , etc. Apart from the excellent performance it is also super easy to use and deploy which makes the experience of using the database very pleasant - we were able to be up and running and storing data within few hours. Topic itself is the QuestDB team that is super responsive on their slack channel and always ready to help with any query. They are constantly improving the product and if there is some missing feature that is blocking you from usage they always try the best to implement such feature asap and release a new version - one of the best support I have ever seen so far in open source community.
Read full review Return on Investment 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 Reduced cost. Increased efficiency. Faster time to market. Read full review ScreenShots