Andreas presents an inside look at the latest Neo4j innovations that enable relationship-driven intelligence at scale. Learn more about the newest cloud integrations and product enhancements that make Neo4j an essential choice for developers building apps with interconnected data and generative AI.
4. Graph Schema: New constraints on nodes,
relationships and properties: Unique relationship
property, Relationship key, Property data types
NEO4J 5.0 NEW CAPABILITIES
Database Enhancements
4
5. Graph Pattern Matching: Improved
expressivity of graph navigation with
quantified path patterns. More powerful and
performant syntax to navigate and traverse
your graph.
NEO4J 5.0 NEW CAPABILITIES
Database Enhancements
5
17. Why RAG With Vector Databases Fall Short
1
3
2
4
Similarity is insufficient for rich enterprise reasoning
Only leverage a fraction of
your data: Beyond simple
“metadata”, vector databases
alone fail to capture relationships
from structured data
Miss critical context: Struggle to
capture connections across
nuanced facts, making it
challenging to answer multi-step,
domain-specific, questions
Vector Similarity ≠ Relevance:
Vector search uses an incomplete
measure of similarity. Relying on it
solely can result in irrelevant and
duplicative results
Lack explainability:
The black-box nature of
vectors lacks transparency
and explainability
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18. Neo4j Inc. All rights reserved 2023
21
RAG with Neo4j
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