Neo4j
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Neo4 is a graph database, that brings data relationships to the fore. From companies offering personalized product and service recommendations; to websites adding social capabilities; to telcos diagnosing network issues; to enterprises reimagining master data, identity, and access models; organizations adopt graph databases as the best way to model, store and query both data and its relationships.
Neo4j Graph Data Science is an analytics and ML engine that uses the relationships in your data to improve predictions. It plugs into enterprise data ecosystems so you can get more data science projects into production quickly. Using pretuned graph algorithms, data scientists can explore billions of data points in seconds to identify hidden connections and generate compelling visualizations that lead to better stakeholder decision making. Practical business applications and operations benefit from the context-first analysis that only graphs can provide across projects like recommendation engines, anomaly and fraud detection, route optimization, marketing, network analysis, and many more.
Neo4j Reviews
Verified User in Computer Software
Neo4j Review: A Great Database to Start with Graph Technologies
Pratik A.
Best Graph Database for your data pattern insight and ML workload
Dipak K.
Solution Analyst | Gen-AI Engineer| ML & DL Enthusiast | GCP ACE | AWS SAA | Databricks | Neo4j Data Science CertifiedLet your data speak using neo4j
About
What is Neo4j?
Neo4j Inc. is a global leader in graph database technology, empowering businesses to harness the power of relationships in data. Founded in 2007, Neo4j is renowned for its robust platform that enables users to build sophisticated applications leveraging data connections, particularly beneficial in areas like fraud detection, real-time recommendations, and network management. The company's flagship product, the Neo4j Graph Database, is available both as a self-hosted solution and a fully managed cloud service. Neo4j's innovative technology supports organizations in visualizing and interpreting complex data relationships, thereby driving intelligent decision-making.