Neo4j

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.

Languages supported: English

8.8/10 (Expert Score) ★★★★★
Product is rated as #9 in category Graph Databases
Ease of use
7.9
Support
8.9
Ease of Setup
7.5

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The fastest path to graph. Centered around the leading native graph database, today’s Neo4j Graph Data Platform is a suite of applications and tools helping the world make sense of data.

The Platform includes the Neo4j Graph Data Science Library – the leading enterprise-ready analytics workspace for graph data available as both open source and through a commercial license for enterprises – the graph visualization and exploration tool Bloom, the Cypher query language – very easy to learn and can operate across Neo4j, Apache Spark and Gremlin-based products using open source toolkits: “Cypher on Apache Spark (CApS) and Cypher for Gremlin.), Neo4j ETL and Kettle for data integration, and numerous additional tools, integrations and connectors to help developers and data scientists build graph-based solutions with ease. And the world’s largest community to help enable any graph journey.

Neo4j is the leading scalable, ACID-compliant graph database designed with a high-performance distributed cluster architecture, available in self-hosted and cloud offerings

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Customer Reviews

Neo4j Reviews

Sana R.

Advanced user of Neo4j
★★★★★
Neo4j for ontology based KB generation

What do you like best?

I've used neo4j for ontology-based KB generation task. So far, I have found neo4j graph-based data representation to be the best fit for such tasks. Apart from that, neo4j easy to learn and operate with.

What do you dislike?

Neo4j master-slave architecture, writes are always done on master. Overall write-performance issues relative to SQL databases. Garbage collection pauses.

Recommendations to others considering the product:

If you think your problem can be solved by graph based data, neo4j is worth a try

What problems are you solving with the product? What benefits have you realized?

I've used neo4j for the ontology-based KB generation task. The knowledge base consists of health care data with ontology representation as disease, symptoms, medication, organ/part of body associated etc along with their respective data and their relationship with each other. applying different graph-ml algorithm (like decision trees) on available data in graph to get a good accuracy of diagnosis. This also focuses on Knowledge Validation, Inferencing and Explanation/ Justification process of knowledge Engineering to maintain our healthcare knowledge base. Currently, we do not have CCDA's available with information of symptom of patients (chief complaint, the reason for visit, etc.). For the time being, we are collecting data from online sources and will use that to symptom-based disease diagnosis.Healthcare KB generation of clinical data using cTAKES NLP and Neo4j.

As name of the project suggests "all men must serve", demo code of the project is available publically in the link. So far, I have found neo4j graph based data representation to be the best fit for such tasks.

Review source: G2.com

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