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Roadmap y Novedades de producto

Neo4j
Neo4j

Jesús Barrasa, Neo4j

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Neo4j Inc. All rights reserved 2023
Roadmap y Novedades de
producto
Jesús Barrasa
Head of Solutions Architecture EMEA
1
Neo4j Inc. All rights reserved 2023 2
…conectando con la intro de Ivan
Neo4j Inc. All rights reserved 2023
The Property Graph Model
3
Employee City
Company
Nodes represent
objects (nouns)
Relationships are directional
Relationships connect nodes are
represent actions (verbs)
Relationships can have properties
(name/value pairs)
Nodes can have
properties (name/value
pairs)
name: Emil Eifrem
date_of_birth: 1979-03-01
employee_ID: 1
:HAS_CEO
start_date: 2008-01-20
:LOCATED_IN
Neo4j Inc. All rights reserved 2023
Cypher (GQL): Pattern Based
4
MATCH (p:Employee {employee_ID: 1})-[r:WORKS_AT*..3]-(c:Company)
RETURN c.name as company, count(*) as score
ORDER BY score DESC
Node
Pattern
Relationship
Pattern
Neo4j Inc. All rights reserved 2023
GQL Standard
5
Project agreed back in September 2019
First version of the full CRUD graph query
language in four-year window
39075 GQL submitted for a DIS (March 24)
Expected publication Q4 2023
Cypher includes GQL features since v.5
DIS = Draft International Standard = technically stable
IS = International Standard.
https://www.iso.org/standard/76120.html
Neo4j Inc. All rights reserved 2023
Neo4j for applications
6
const movies = await driver
.executeQuery(
'match (p:Employee)-[r:WORKS_AT*..3]-(c:Company) return c',{limit: 10})
.then((result) => { return result.records.map( (r) => r.get('c') ) })
.catch((error) => { console.error(error) })

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Roadmap y Novedades de producto

  • 1. Neo4j Inc. All rights reserved 2023 Roadmap y Novedades de producto Jesús Barrasa Head of Solutions Architecture EMEA 1
  • 2. Neo4j Inc. All rights reserved 2023 2 …conectando con la intro de Ivan
  • 3. Neo4j Inc. All rights reserved 2023 The Property Graph Model 3 Employee City Company Nodes represent objects (nouns) Relationships are directional Relationships connect nodes are represent actions (verbs) Relationships can have properties (name/value pairs) Nodes can have properties (name/value pairs) name: Emil Eifrem date_of_birth: 1979-03-01 employee_ID: 1 :HAS_CEO start_date: 2008-01-20 :LOCATED_IN
  • 4. Neo4j Inc. All rights reserved 2023 Cypher (GQL): Pattern Based 4 MATCH (p:Employee {employee_ID: 1})-[r:WORKS_AT*..3]-(c:Company) RETURN c.name as company, count(*) as score ORDER BY score DESC Node Pattern Relationship Pattern
  • 5. Neo4j Inc. All rights reserved 2023 GQL Standard 5 Project agreed back in September 2019 First version of the full CRUD graph query language in four-year window 39075 GQL submitted for a DIS (March 24) Expected publication Q4 2023 Cypher includes GQL features since v.5 DIS = Draft International Standard = technically stable IS = International Standard. https://www.iso.org/standard/76120.html
  • 6. Neo4j Inc. All rights reserved 2023 Neo4j for applications 6 const movies = await driver .executeQuery( 'match (p:Employee)-[r:WORKS_AT*..3]-(c:Company) return c',{limit: 10}) .then((result) => { return result.records.map( (r) => r.get('c') ) }) .catch((error) => { console.error(error) })
  • 7. Neo4j Inc. All rights reserved 2023 Neo4j for analytics 7 from graphdatascience import GraphDataScience gds = GraphDataScience(DB_ULR, auth=(DB_USER, DB_PASS)) gds.louvain.write(G,writeProperty='community')
  • 8. Neo4j Inc. All rights reserved 2023 Neo4j: Native graph architecture 8 Native Graph Storage Native Graph Processing Autonomous Clustering Composite Databases • No mismatch • Data integrity / ACID • Schema flexible • 1000x faster than relational • K-Hop now 10-1000x faster than version 4 • Elastic scale-out for high throughput • 100s of machines across clusters • Federation of scaled out shards • Instant composite database Data is connected as it is stored Lightning-fast retrieval of data and relationships via pointer chasing
  • 9. © 2023 Neo4j, Inc. All rights reserved. New in Neo4j 5 - recap 9
  • 10. © 2023 Neo4j, Inc. All rights reserved. Graph Schema: New constraints on nodes, relationships and properties: Unique relationship property, Relationship key, Property data types NEO4J 5.0 NEW CAPABILITIES Database Enhancements 10
  • 11. © 2023 Neo4j, Inc. All rights reserved. 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 11
  • 12. © 2023 Neo4j, Inc. All rights reserved. MATCH path=(a:Account)-[rel:TRANSACTION*3..6]->(a) WHERE size(apoc.coll.toSet(nodes(path))) = size(nodes(path)) - 1 AND ALL(idx in range(0, size(rel)-2) WHERE (rel[idx]).date < (rel[idx+1]).date AND (rel[idx+1].amount / rel[idx].amount) * 100 <= 20 ) RETURN path NEO4J 5.0 NEW CAPABILITIES Database Enhancements Graph Pattern Matching Example 12 Pre-QPP
  • 13. © 2023 Neo4j, Inc. All rights reserved. MATCH path=(a:Account)-[:PERFORMS]->(first_tx) ((tx_i)-[:BENEFITS_TO]->(a_i)-[:PERFORMS]->(tx_j) WHERE tx_i.date < tx_j.date AND 0.80 <= tx_i.amount / tx_j.amount <= 1.00 ){3,6} (last_tx)-[:BENEFITS_TO]->(a) WHERE size(apoc.coll.toSet([a]+a_i)) = size([a]+a_i) RETURN path NEO4J 5.0 NEW CAPABILITIES Database Enhancements Graph Pattern Matching Example 13 QPP
  • 14. © 2023 Neo4j, Inc. All rights reserved. Call in Transactions: for batched import, control transaction sizes from Cypher. Incremental Importer: Ultra-high speed method of loading data incrementally (10-100x faster than transactional). NEO4J 5.0 NEW CAPABILITIES Database Enhancements 14
  • 15. © 2023 Neo4j, Inc. All rights reserved. Backup & Recovery: Existing full backups can be updated with differential data instead of recreating a new full backup, saving a large amount of storage. Administrators can now execute point-in-time restore. API to ease operability Neo4j Ops Manager: To monitor Neo4j deployments NEO4J 5.0 NEW CAPABILITIES Database Enhancements 15
  • 16. © 2023 Neo4j, Inc. All rights reserved. Luis nos va a dar todos los detalles en su presentación NEO4J 5.0 NEW CAPABILITIES Vector Index 16
  • 17. © 2023 Neo4j, Inc. All rights reserved. Parallel Runtime 17
  • 18. © 2023 Neo4j, Inc. All rights reserved. NEO4J 5.0 NEW CAPABILITIES Parallel Runtime: Speed up analytical query up to 100x 18
  • 19. © 2023 Neo4j, Inc. All rights reserved. Parallel Runtime Speedup Up to 100x faster analytical queries by adding CPU cores 19 More cores Faster Queries
  • 20. © 2023 Neo4j, Inc. All rights reserved. Change Data Capture (CDC) 20
  • 21. © 2023 Neo4j, Inc. All rights reserved. NEO4J 5.0 NEW CAPABILITIES Change Data Capture: Automated Real-Time Change Tracking 21
  • 22. © 2023 Neo4j, Inc. All rights reserved. Integration Google Dataflow 22
  • 23. © 2023 Neo4j, Inc. All rights reserved. GCP Dataflow integration 23 https://neo4j.com/docs/dataflow-google-cloud/ https://neo4j.com/docs/dataflow-bigquery/
  • 24. © 2023 Neo4j, Inc. All rights reserved. Looking Ahead: Auto-Sharding 24
  • 25. © 2023 Neo4j, Inc. All rights reserved. NEO4J 5.0 NEW CAPABILITIES Fabric Auto-Sharding 25 Coming 2024+ Mapping Sharding Rules
  • 26. © 2023 Neo4j, Inc. All rights reserved. NEO4J 5.0 NEW CAPABILITIES Fabric Auto-Sharding 26 Coming 2024+ Mapping Sharding Rules ● Leverage customer hints to create sharding strategy ● Enable creation of schema/metadata for sharding ● Automatically increase shards based on customer configuration ● Create Fabric planner to push data and queries to right shards ● Overtime support distributed transactions & proxy nodes ● Make it available in Aura
  • 27. © 2023 Neo4j, Inc. All rights reserved. Graph Data Science News 27
  • 28. Edge embeddings Find missing relationships ● Users generate edge embeddings using DGL, PyKeen, or PyTorch Geometric ● Bring them into Neo4j Graph Data Science or AuraDS stored as a property. ● Use similarity functions to identify possible relationship candidates and check node pairs. ● Create relationships Help predict missing relationships between entities Infer new relationships Improve semantic understanding and reasoning Neo4j Inc. All rights reserved 2023 28 How it Helps You
  • 29. Longest Path Algo Find the path of maximum length between two nodes in a directed acyclic graph Neo4j Inc. All rights reserved 2023
  • 30. Longest Path Once a directed acyclic graph is built, use either Graph Data Science or the Python client to call the Longest Path Algorithm. Find the path of maximum length between two nodes in a graph. Help solve critical scheduling and optimization problems by understanding longest paths How it Helps You
  • 31. Topological Sort Algo Sort nodes in a directed acyclic graph by traversing them in order of dependency Identify dependencies Neo4j Inc. All rights reserved 2023
  • 32. Identify Dependencies Once a directed acyclic graph is built, use either Graph Data Science or the Python client to call the topological sort algorithm. Find dependencies in the graph. Ensure that dependent tasks are performed in the correct order How it Helps You
  • 33. © 2023 Neo4j, Inc. All rights reserved. Thank You! See you 9th April 2024 at our next GraphSummit Madrid! 33