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© 2022 Neo4j, Inc. All rights reserved.
© 2022 Neo4j, Inc. All rights reserved.
The Neo4j Graph Data Platform
Today & Tomorrow
© 2022 Neo4j, Inc. All rights reserved.
2
Exponential Growth in Connected Data
Connected data use-
cases are exploding in
numbers and in depth
Data models the real
world. Therefore data is
becoming increasingly
connected.
The world is
becoming
increasingly
connected
© 2022 Neo4j, Inc. All rights reserved.
Graphs Embody Real World Context
• Easily understood
• Easily adapted
• Streamlines collaboration between
business and IT
Context: Faster Insights and Deeper Understanding
3
© 2022 Neo4j, Inc. All rights reserved.
Relational Databases
Don’t handle relationships well
● Not well adapted to interconnected semi-structure
● Schema rigidity limits business agility
● Relationship queries require painful SQL & joins
● Practically limited to three degrees of separation
Other NOSQL Databases
Don’t handle relationships at all
● Built to scale simple data (store & retrieve)
● No language or structures for handling relationships:
joins done through the application
● ACID is very implementation dependent
Graph Databases
Natively store, query relationships
● Data model purpose-built for graphs
● Powerful balance of schema flexibility & structure
● Highly powerful & productive query language
● Queries run 1000x faster at scale, up to 1000+
degrees of separation
Graph Databases Unlock New Data Possibilities
“We found Neo4j to be literally thousands of times faster than our prior MySQL solution, with
queries that require 10-100 times less code. Today, Neo4j provides eBay with functionality
that was previously impossible.” --- Volker Pacher, Senior Staff Engineer
4
4
© 2022 Neo4j, Inc. All rights reserved.
The Neo4j Graph Data Platform
Runs Anywhere
Deploy as-a-Service (AuraDB) or
self-hosted within your cloud of
choice (AWS, GCP, Azure) via their
marketplace, or on-premises.
Development Tools &
Frameworks
Tooling, APIs, query builder,
multi-language support for
development, admin, modeling,
and rapid prototyping needs.
Data Science and Analytics
Explorative tools, rich algorithm library,
and Integrated supervised Machine
Learning framework.
Native Graph Database
The foundation of the Neo4j platform;
delivers enterprise-scale and
performance, security, and data
integrity for transaction and analytical
workloads.
Graph Query Language
Cypher & openCypher; Ongoing
leadership and standards work (GQL)
to establish lingua franca for graphs.
Discovery & Visualization
Code-free querying, data modeling and
exploration tools for data scientists,
developers, and analysts.
Ecosystem & Integrations
Rich ecosystem of tech and
integration partners. Ingestion tools
(JDBC, Kafka, Spark, BI Tools, etc.) for
bulk and streaming needs.
5
© 2022 Neo4j, Inc. All rights reserved.
Neo4j: A Rich History of Graph Innovation
6
2020 - 2022
● Graph-RBAC Security, the First and
Most Advanced of Its Kind
● First Native & Fully Integrated Graph
Data Science Offering
● First In-Graph Machine Learning
Technology
● Neo4j Fabric, the First Enterprise
Graph Scaling Architecture for
Sharding & Federation
2015 - 2019
● openCypher: the De Facto Open
Source Graph Standard
● Graph Algorithms for Data Science
● Bloom for Rich Data Visualization and
Exploration
● Active Participant in ISO GQL
Standard, initiated by Neo4j
● AuraDB: First Native Graph DB as-a-
Service
2010 - 2014
● Pioneered the Graph Database Category
● First Native Graph Database:
Open Source, Built for Property Graphs
● Introduced Cypher Graph Query
Language
● Evolved Property Graph Model with
Labels, Geospatial & More
6

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The Neo4j Data Platform for Today & Tomorrow.pdf

  • 1. © 2022 Neo4j, Inc. All rights reserved. © 2022 Neo4j, Inc. All rights reserved. The Neo4j Graph Data Platform Today & Tomorrow
  • 2. © 2022 Neo4j, Inc. All rights reserved. 2 Exponential Growth in Connected Data Connected data use- cases are exploding in numbers and in depth Data models the real world. Therefore data is becoming increasingly connected. The world is becoming increasingly connected
  • 3. © 2022 Neo4j, Inc. All rights reserved. Graphs Embody Real World Context • Easily understood • Easily adapted • Streamlines collaboration between business and IT Context: Faster Insights and Deeper Understanding 3
  • 4. © 2022 Neo4j, Inc. All rights reserved. Relational Databases Don’t handle relationships well ● Not well adapted to interconnected semi-structure ● Schema rigidity limits business agility ● Relationship queries require painful SQL & joins ● Practically limited to three degrees of separation Other NOSQL Databases Don’t handle relationships at all ● Built to scale simple data (store & retrieve) ● No language or structures for handling relationships: joins done through the application ● ACID is very implementation dependent Graph Databases Natively store, query relationships ● Data model purpose-built for graphs ● Powerful balance of schema flexibility & structure ● Highly powerful & productive query language ● Queries run 1000x faster at scale, up to 1000+ degrees of separation Graph Databases Unlock New Data Possibilities “We found Neo4j to be literally thousands of times faster than our prior MySQL solution, with queries that require 10-100 times less code. Today, Neo4j provides eBay with functionality that was previously impossible.” --- Volker Pacher, Senior Staff Engineer 4 4
  • 5. © 2022 Neo4j, Inc. All rights reserved. The Neo4j Graph Data Platform Runs Anywhere Deploy as-a-Service (AuraDB) or self-hosted within your cloud of choice (AWS, GCP, Azure) via their marketplace, or on-premises. Development Tools & Frameworks Tooling, APIs, query builder, multi-language support for development, admin, modeling, and rapid prototyping needs. Data Science and Analytics Explorative tools, rich algorithm library, and Integrated supervised Machine Learning framework. Native Graph Database The foundation of the Neo4j platform; delivers enterprise-scale and performance, security, and data integrity for transaction and analytical workloads. Graph Query Language Cypher & openCypher; Ongoing leadership and standards work (GQL) to establish lingua franca for graphs. Discovery & Visualization Code-free querying, data modeling and exploration tools for data scientists, developers, and analysts. Ecosystem & Integrations Rich ecosystem of tech and integration partners. Ingestion tools (JDBC, Kafka, Spark, BI Tools, etc.) for bulk and streaming needs. 5
  • 6. © 2022 Neo4j, Inc. All rights reserved. Neo4j: A Rich History of Graph Innovation 6 2020 - 2022 ● Graph-RBAC Security, the First and Most Advanced of Its Kind ● First Native & Fully Integrated Graph Data Science Offering ● First In-Graph Machine Learning Technology ● Neo4j Fabric, the First Enterprise Graph Scaling Architecture for Sharding & Federation 2015 - 2019 ● openCypher: the De Facto Open Source Graph Standard ● Graph Algorithms for Data Science ● Bloom for Rich Data Visualization and Exploration ● Active Participant in ISO GQL Standard, initiated by Neo4j ● AuraDB: First Native Graph DB as-a- Service 2010 - 2014 ● Pioneered the Graph Database Category ● First Native Graph Database: Open Source, Built for Property Graphs ● Introduced Cypher Graph Query Language ● Evolved Property Graph Model with Labels, Geospatial & More 6
  • 7. © 2022 Neo4j, Inc. All rights reserved. Guiding Beacons Performance at Scale "Minutes to Milliseconds” Performance: Queries that take seconds/minutes/hours run in milliseconds on Neo4j Business impact: enables entirely new forms of value creation, not otherwise possible Agility - Flexible Schema Flexible schema enables the database to adapt to an evolving business, rapidly and without disruption Business impact: projects deliver more, in less time, with less risk Developer Productivity Cypher enables more with less: 10x less code than SQL. Direct path to an ISO standard. World’s largest community of skilled graph developers Business impact: projects deliver more, in less time, with less risk Resource Efficiency Often requires 10x less resources than other graph databases, particularly those built on relational, NoSQL, and RDF databases Business Impact: significant bottom-line savings & TCO reduction Transactions Analytics 7
  • 8. © 2022 Neo4j, Inc. All rights reserved. Neo4j Fabric 9 UNWIND demo.graphIds() AS gid CALL { USE demo.graph( gid ) MATCH ( u:User ) RETURN max( u.age ) AS localMaxAge } RETURN MAX( localMaxAge ) AS globalMaxAge Unlimited Scalability for Sharded and Federated Graphs Users queries are executed in parallel on any graph. Graph selection can be pruned by sharding logic. Results are retrieved and aggregated, then returned to the user or written to other graphs.
  • 9. © 2022 Neo4j, Inc. All rights reserved. 10 30 Billion 1.2 Trillion! 128 Billion Neo4j Fabric: Scaling Up & Scaling Out!
  • 10. © 2022 Neo4j, Inc. All rights reserved. FAST ● Real-time Performance at Scale ● Automatic Upgrades, Patches, Backups ● Scale on Demand, No Downtime ● High Availability ● Multi Cloud, Any Region ● Enterprise-grade Security ● Simple Capacity Based Pricing ● 24/7 Premium Support FAST FLEXIBLE RELIABLE EASY Self-hosted Available AuraDB Coming Soon Fully-managed Cloud Service 11
  • 11. © 2022 Neo4j, Inc. All rights reserved. Free Professional Enterprise Self-Start For Developers For Data Scientists Graph Database as a Service Graph Data Science as a Service Neo4j as a Service Offerings Enterprise 2H-2022 EAP EOY-2022 2H-2022 EAP, 2H-2022 GA
  • 12. © 2022 Neo4j, Inc. All rights reserved. Aura: Enterprise Grade Security & Management Single Sign-On Cyber Academy Code Scanning & Pentesting Secure Development Practices Dedicated VPC AWS PrivateLink Private Service Connect (GCP - 2H 2022) Role- & Schema-Based Access Control Node, Edge, and Traversal Level Granularity Encryption (At-Rest, In-Transit, and Intra Cluster) TLS 1.2/1.3, with encrypted bucket storage
  • 13. © 2022 Neo4j, Inc. All rights reserved. Neo4j Meets All Your Regulatory Compliance Needs 14 SOC 2 Type I ISO 27001 Certified Coming H2 2022
  • 14. © 2022 Neo4j, Inc. All rights reserved. 15 New! Data Warehouse Connector ● Make it easier than ever to move data between your data warehouse and Neo4j ● Support for Snowflake, Google BigQuery, Amazon RedShift, and Azure Synapse ● Use as a: ○ Spark Submit Job (provide JSON configuration) ○ Simplified Scala/Python API Data Warehouse Connector
  • 15. © 2022 Neo4j, Inc. All rights reserved. 16 Full Breadth of Connector & Language Support Neo4j BI Connector Apache Spark Connector Apache Kafka Connector Data Warehouse Connector Java Python .NET JavaScript Go
  • 16. © 2022 Neo4j, Inc. All rights reserved. Neo4j Graph Data Tools For All Access your Neo4j database locally Access your Neo4j database from your browser Visualize and explore your Neo4j database Build intelligent applications faster with a Neo4j graph database
  • 17. © 2022 Neo4j, Inc. All rights reserved. 18 New in Neo4j Graph Data Platform 18
  • 18. © 2022 Neo4j, Inc. All rights reserved. Data Importer: Model & Load Your First Graph ● Intuitive data modeling UI ● Map flat files to graphs ● Built to import up to millions of records ● Import directly Neo4j Aura or self-managed 19
  • 19. © 2022 Neo4j, Inc. All rights reserved. 20 Neo4j Ops Manager Manage all Neo4j deployments centrally Dashboard covering top metrics for OS, DBMS, and Database Dedicated UIs for managing Role Based Access Control, Upgrades, and more
  • 20. © 2022 Neo4j, Inc. All rights reserved. © 2022 Neo4j, Inc. All rights reserved. Neo4j Graph Data Science 21
  • 21. © 2022 Neo4j, Inc. All rights reserved. What’s Unusual? What’s Important? What’s Next? Graph Data Science Helps Make Sense of Your Data Relationships 22 Exploring the hidden patterns and features in your data
  • 22. © 2022 Neo4j, Inc. All rights reserved. 23 Graphs Contain Implicit Knowledge Which of the colored nodes would be considered the most ‘important' ?
  • 23. © 2022 Neo4j, Inc. All rights reserved. 24 Graph Algorithms Help Unlock This Knowledge D D has the highest valence This is the most connected individual in the network. If importance is how well you are personally known you pick D. G has the highest closeness centrality (0.52) Information will disperse through the network more quickly through this individual. If you need to get a message out rapidly, choose them. G I has the highest betweenness centrality (0.59) This person is an efficient connector of other people. Risk of network disruption is higher if you lose this individual. I Most Important?
  • 24. © 2022 Neo4j, Inc. All rights reserved. 25 The Domains of Graph Data Science Graph Native Machine Learning Learn features in your graph that you don’t even know are important yet using embeddings. Predict links, labels, and missing data with in-graph supervised ML models. Identify associations, anomalies, and trends using unsupervised machine learning. Graph Algorithms Knowledge Graphs Find the patterns you’re looking for in connected data
  • 25. © 2022 Neo4j, Inc. All rights reserved. 26 The easiest graph data science platform Easy to use ●Automated MLOps ●Runs Anywhere ●Cloud Commitments Built by data scientists, for data scientists Data Scientists ● Native Python Client ● 65+ Graph Algos ● ML Pipelines Go to production with speed, security, and scale Enterprise Ready ● 8M Objects/sec Load ● RBAC Security ● Designed to Scale Fits into your data stack and pipeline Ecosystem ●BI tools, Apache Spark, Kafka, Data Warehouses ●Vertex AI, SageMaker, Synapse Neo4j Graph Data Science 26
  • 26. © 2022 Neo4j, Inc. All rights reserved. The Neo4j Native Graph Catalog • Automates data transformations • Experiment with different data sets, data models • Fast iterations & layering • Production ready features, parallelization & enterprise support • Ability to persist and version trained models A graph-specific analytics workspace that’s mutable – integrated with Neo4j’s native-graph database Mutable In-Memory Workspace Graph Projection Native Graph Store
  • 27. © 2022 Neo4j, Inc. All rights reserved. 28 The Largest Catalog of Graph Algorithms Pathfinding & Search Centrality & Importance Community Detection Supervised Machine Learning Heuristic Link Prediction Similarity Graph Embeddings …and more Over 65 Pretuned, Parallelized Algorithms
  • 28. © 2022 Neo4j, Inc. All rights reserved. 29 From Chaos to Structure: Neo4j Graph Data Science is Changing How Machine Learning Gets Done Graph Embeddings summarize the enhanced explicit knowledge of a graph
  • 29. © 2022 Neo4j, Inc. All rights reserved. © 2022 Neo4j, Inc. All rights reserved. 30 “50% of Gartner inquiries on the topic of AI involve discussion of the use of graph technology.” Top 10 Tech Trends in Data and Analytics 2021 AI Research Papers Featuring Graph Source: Dimensions Knowledge System
  • 30. © 2022 Neo4j, Inc. All rights reserved. 31 Real World Data, Real World Fraud Detection • Real, anonymized customer data set • Using Neo4j Graph Data Science • Blog post with sample code available https://neo4j.com/developer-blog/exploring-fraud-detection-neo4j-graph-data-science-summary/ Exploring Fraud Detection With Neo4j & Graph Data Science Zach Blumenfeld Data Science Product Specialist, Neo4j 87% More fraud risks detected!
  • 31. © 2022 Neo4j, Inc. All rights reserved. 32 Logistics and Supply Chain Plan maritime routes based on distances, costs, and internal logic. Results: ● Subsecond maritime routes planning ● Reduce global carbon emissions 60,000 tons ● 12-16M ROI for OrbitMI customers
  • 32. © 2022 Neo4j, Inc. All rights reserved. 33 New in Neo4j Graph Data Science 33
  • 33. © 2022 Neo4j, Inc. All rights reserved. 34 Machine Learning Pipelines Graph Native ML Pipelines: ● Node Classification ● Node Regression (new!) ● Link Prediction Trained Models & the Model Catalog: ● Save, persist & publish trained models ● Instantly apply for prediction on new and existing data in the graph Guided & Automated Pipeline Features: ● Data splitting & rebalancing ● Feature engineering ● Model evaluation and selection ● Automated hyperparameter tuning (new!) What we do : Link Prediction Example Define a pipeline, add the steps you want to perform, and we handle the rest for you.
  • 34. © 2022 Neo4j, Inc. All rights reserved. 35 New! Apache Arrow Integration ● Import and export massive graphs directly in and out ● Fast graph projections (from external sources) ● Database creation & algorithm result export Up to 30 million objects/second
  • 35. © 2022 Neo4j, Inc. All rights reserved. New! Native Graph Data Science Python Client 36 ● Simplifies workflows for data scientists ● Run Graph Data Science algorithms just like any Python function ● Eliminates the need for transaction functions for data science ● Pythonic features support for graph and model objects
  • 36. © 2022 Neo4j, Inc. All rights reserved. 37 New! Graph Data Science As-a-Service ● Handles all DB management for you ● Simple to scale up or down ● Paused instance to save ● Starts at $1/hour Enterprise ready, with fully managed infrastructure, updates, and security patches
  • 37. © 2022 Neo4j, Inc. All rights reserved. New! Explore Graph Algorithms Directly in Bloom 38
  • 38. © 2022 Neo4j, Inc. All rights reserved. © 2022 Neo4j, Inc. All rights reserved. Neo4j: Up and Coming Sneak Peak 39
  • 39. © 2022 Neo4j, Inc. All rights reserved. Safe Harbor Roadmap Disclaimer The information presented here is Neo4j, Inc. confidential and does not constitute, and should not be construed as, a promise or commitment by Neo4j to develop, market or deliver any particular product, feature or function. Neo4j reserves the right to change its product plans or roadmap at any time, without obligation to notify any person of such changes. The timing and content of Neo4j’s future product releases could differ materially from the expectations discussed herein. 40
  • 40. © 2022 Neo4j, Inc. All rights reserved. Rich Capabilities We’re always innovating with cutting edge features to power your business We make graph easy, so you can focus on building business value Frictionless Experience Enterprise Grade We prioritize trust in the platform; secure, reliable, available, and operable 41 Guiding Roadmap Principles
  • 41. © 2022 Neo4j, Inc. All rights reserved. Accelerating Bulk Updates Even Faster 42 Incremental Import Rich Capabilities High performance bulk load into existing databases Bulk updates are as easy as 1-2-3 1. Load updates in a separate database (with the same performance of a new load) 2. Prepare data for a merge into an existing database 3. Merge updates into another database …or execute all in one step Differential data can be saved for multiple updates
  • 42. © 2022 Neo4j, Inc. All rights reserved. Workspace: Unified Experience for Neo4j Frictionless Experience Unified Workspace A single workspace to unify the experience of all developer tools 43 EAP Sign-up! https://neo4j.com/workspace
  • 43. © 2022 Neo4j, Inc. All rights reserved. 44 44
  • 44. © 2022 Neo4j, Inc. All rights reserved. Cypher in Neo4j 5: More Expressive Advanced Pattern Matching Frictionless Experience Advanced Pattern Matching Deconstruct paths, solve each part, reassemble to form the overall path MATCH (t:Part {id:"120-001"}) ((:Part)<-[:BELONGS_TO]-(:Part))* (mc:Part WHERE COALESCE(mc.cost, mc.part_cost) IS NULL) ((:Part)<-[r:BELONGS_TO]-(hc:Part) WHERE COALESCE(hc.cost, hc.part_cost) IS NOT NULL)+ WITH mc, SUM(r.qty * COALESCE(hc.cost, hc.part_cost)) AS part_cost SET mc.part_cost = part_cost 1 2 3 4 Bill of Materials with Advanced Pattern Matching 45
  • 45. © 2022 Neo4j, Inc. All rights reserved. New GraphQL UI: Coming in 2H 2022 GraphQL UI Frictionless Experience Low-code UI for prototyping and exploring the GraphQL schema 46
  • 46. © 2022 Neo4j, Inc. All rights reserved. Autonomous Clustering in Neo4j 5 47 Maximum scalability and on-demand infrastructure Databases with independent functionality for availability and performance Always online, with rolling upgrades and Fabric integration Accessible from anywhere, in VPCs as well as publicly exposed when needed Neo4j 5 Cluster Enterprise Grade Flexible Clustering Fabric, parallel implementations, performance proof points
  • 47. © 2022 Neo4j, Inc. All rights reserved. 48 Other Data Stores Transactions Analytics Graph Database Graph Data Science Integrated AI/Machine Learning Data Integrations & Connectors Admin Cypher Drivers & APIs Dev Tools Application Layer: Digital Twin, Recommendation, Fraud Detection, Cybersecurity, … Query Browser GraphQL Analytics & AI/Machine Learning Pipelines The Neo4j Graph Data Platform Flexible Graph Schema Performance, Reliability & Integrity Scale-Up & Scale-Out Architecture Development Tools Breadth Enterprise Ecosystem
  • 48. © 2022 Neo4j, Inc. All rights reserved. © 2022 Neo4j, Inc. All rights reserved. 49 Thank you! Contact us at sales@neo4j.com
  • 49. © 2022 Neo4j, Inc. All rights reserved. © 2022 Neo4j, Inc. All rights reserved. 50 Slide Bucket Contact us at sales@neo4j.com
  • 50. © 2022 Neo4j, Inc. All rights reserved. 52 Fast, Actionable Insights you couldn’t find without graph Find patterns Make predictions Explore and share Move to production Analytics Feature Engineering Data Exploration Graph Data Science Queries Machine Learning Visualization
  • 51. © 2022 Neo4j, Inc. All rights reserved. 58 ● Boston Scientific needed a more efficient method for finding the root causes of quality control problems. ● The heart of Boston Scientific’s graph data model consists of three nodes representing a finished product, a part and an issue, with relationships that trace problems to parts and connect those to finished products. ● The Boston Scientific team analyzes its graph and computes scores that rank nodes based on their proximity to failures, enriching its models with insights derived from the graph.
  • 52. © 2022 Neo4j, Inc. All rights reserved. 59 Neo4j: Innovating in Graph Technology Transactional AND analytical workloads Transactions Analytics In memory graph processing to support algos and machine learning Incredibly rich and powerful tools and integrations Robust security, w. SSO VPC peering, fine grained RBAC, regulatory compliance Run anywhere design - on- premises, self- hosted, GCP, AWS, and Azure
  • 53. © 2022 Neo4j, Inc. All rights reserved. 60 Graphs Databases: Optimized for Today’s Data Needs ● Creates context for decisions ● Single entity focus ● Historical & real-time data ● API with singleton queries ● Reporting integration ● Foundation for graph recos X360° Graphs ● Creates holistic view of business ● Pulls data from multiple sources ● Unifies data across silos ● Consistent naming conventions ● Mobilizes data in data lakes ● Supports apps, reports, APIs Enterprise Knowledge Graphs ● Enables E2E process optimization ● Focus on flows, movement ● Hierarchies and cascades ● Easily handles recursion ● Identifies dependencies ● Traces journeys Process Graphs ● Reveals risks hidden in data ● Leverages graph inference ● Depicts complex relationships ● Reveals anomalous patterns ● Automated alerts in real-time ● Ad-hoc forensics Risk Graphs A B C D E