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Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.
Which is more popular?
Based on our record, neo4j seems to be more popular. It has been mentioned 36 times since March 2021.
Website, pricing, platforms and company facts side by side.
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| Website | fullstacktoolkit.com | neo4j.com |
| Pricing | — | |
| Company | — | Startup from the United States · 500 - 999 employees · 2007 |
| Listed in |
What each product offers, as listed by its team.


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An editorial look at what each product does well and who it suits.


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All about GRAND Stack: GraphQL, React, Apollo, and Neo4j
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Share your experience with using FullStackToolkit and neo4j. For example, how are they different and which one is better?
External articles and on-site reviews we used to compare the two products.


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Neo4j is an open-source graph database, implemented in Java described as embedded, disk-based, fully transactional Java persistence engine that stores data structured in graphs rather than in tables. Neo4j Community...
Multi-Model: Neo4j is a single-model graph database. It does not support any other data models. If your application requires a document or key/value store, you would have to use a second database technology to support...
Recommendations tracked on public social media and blogs since March 2021.


Tracking FullStackToolkit since Sep 2026.
The stack runs on Qdrant for vector storage, Ollama for local embeddings, and optional Neo4j for a knowledge graph that I added later. I also set it up to route different operations to the best LLM for each task. It provides eleven tools... - Source: dev.to / 7 months ago
Perhaps the biggest promoter of the term has been Philip Rathle from Neo4j, which offers the best-known graph database system for storing knowledge graphs. But here's where the confusion starts: Is a knowledge graph something you store,... - Source: dev.to / 9 months ago
The key difference lies in the retrieval mechanism. Vector databases focus on semantic similarity by comparing numerical embeddings, while graph databases emphasize relations between entities. Two solutions for graph databases are... - Source: dev.to / over 1 year ago
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