Best Graph Database for your data pattern insight and ML workload
What do you like best about the product?
the cypher syntax of neo4j is really great for beginners, it is as similar as human communicating with db in english langauage. it's just that we have to express in a correct manner for e.g if i want to retrieve all the persons with a gender male it's cypher syntax will be
Match (p: Person { Gender:"Male"} ) return p )
Neo4j's Browser and Bloom feature gives business stakeholder and data scientist/analyst to analyze their data which i think currently no other database give at this moment
and on top of that they have their own graph data science library which gives feasibility in developing application such as link prediction, recommendation system, chatbots
Match (p: Person { Gender:"Male"} ) return p )
Neo4j's Browser and Bloom feature gives business stakeholder and data scientist/analyst to analyze their data which i think currently no other database give at this moment
and on top of that they have their own graph data science library which gives feasibility in developing application such as link prediction, recommendation system, chatbots
What do you dislike about the product?
I think they should add more compute storage for Aura DB, as our system can load 100s of GB data in neo4j , but currently i dont see any option for
What problems is the product solving and how is that benefiting you?
I have expertise in building analytical solution which speaks insights from client data , it's amazing speed of retrieval from billions of nodes and relationships is one of the reason for choosing neo4j for big data and complex relationship analysis. to be more specific we have used neo4j aura 8gb ram instance which gives us feasibility to store millions of nodes and relationships and the best thing about is infrastructure is completely managed by neo4j aura. clients are able to take better business decision based on the visual representation of nodes and relationships, we use neovis.js library for representing these data in the form of nodes and relationship and abstracting the technical logic and ensuring the security of data layer and then using algorithms like Fast RP Embeddings we created recommendation engine easily, thank you neo4j.
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