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Graph Data Processing with Cypher

You're reading from  Graph Data Processing with Cypher

Product type Book
Published in Dec 2022
Publisher Packt
ISBN-13 9781804611074
Pages 332 pages
Edition 1st Edition
Languages
Concepts
Author (1):
Ravindranatha Anthapu Ravindranatha Anthapu
Profile icon Ravindranatha Anthapu

Table of Contents (18) Chapters

Preface 1. Part 1: Cypher Introduction
2. Chapter 1: Introduction to Neo4j and Cypher 3. Chapter 2: Components of Cypher 4. Part 2: Working with Cypher
5. Chapter 3: Loading Data with Cypher 6. Chapter 4: Querying Graph 7. Chapter 5: Filtering, Sorting, and Aggregations 8. Chapter 6: List Expressions, UNION, and Subqueries 9. Part 3: Advanced Cypher Concepts
10. Chapter 7: Working with Lists and Maps 11. Chapter 8: Advanced Query Patterns 12. Chapter 9: Query Tuning 13. Chapter 10: Using APOC Utilities 14. Chapter 11: Cypher Ecosystem 15. Chapter 12: Tips and Tricks 16. Index 17. Other Books You May Enjoy

Summary

In this chapter, we took a deeper look at Neo4j internals to understand how a database works to execute queries. We also reviewed a few query patterns and saw the right and wrong ways to build queries and looked at troubleshooting common issues.

Cypher is an easy language to learn compared to SQL. However, it takes a bit of an effort to get the most out of it. One thing to remember is that Neo4j is a schemaless storage. This gives us great flexibility when it comes to data modeling. If your application use case starts changing, the current data model becomes too limiting, and your queries get slower, there is no need to create a completely new model. You can start adapting the existing model by adding new model concepts, thus keeping the same graph for the old and new functionality. Once you are satisfied with new model changes, it is possible to remove the remnants of the old model that are not required. Combining this kind of model flexibility with the simplicity and power...

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