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![Cypher: Powerful and Expressive Query Language
MATCH (:Person { name:“Dan”} ) -[:LOVES]-> (:Person { name:“Ann”} )
LOVES
Dan Ann
LABEL PROPERTY
NODE NODE
LABEL PROPERTY](https://image.slidesharecdn.com/neo4jatlantagraphtalk09082016-160921141445/85/Introducing-Neo4j-17-320.jpg)
![MATCH (boss)-[:MANAGES*0..3]->(sub),
(sub)-[:MANAGES*1..3]->(report)
WHERE boss.name = “John Doe”
RETURN sub.name AS Subordinate,
count(report) AS Total
Express Complex Queries Easily with Cypher
Find all direct reports and how
many people they manage,
up to 3 levels down
Cypher Query
SQL Query](https://image.slidesharecdn.com/neo4jatlantagraphtalk09082016-160921141445/85/Introducing-Neo4j-18-320.jpg)
Uploaded byNeo4j
Introducing Neo4j
This document summarizes a presentation about the graph database Neo4j. The presentation included an agenda that covered graphs and their power, how graphs change data views, and real-time recommendations with graphs. It introduced the presenters and discussed how data relationships unlock value. It described how Neo4j allows modeling data as a graph to unlock this value through relationship-based queries, evolution of applications, and high performance at scale. Examples showed how Neo4j outperforms relational and NoSQL databases when relationships are important. The presentation concluded with examples of how Neo4j customers have benefited.
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Introducing Neo4j
- 1. Introducing Neo4j The GraphDatabase Atlanta GraphTalk September 8th, 2016
- 2. Todays Agenda • 2:30- 3:00: Registration and Coffee • 3:00 - 3:45: Graphs in Action: An introduction to the power of graph databases • 3:45- 4:15: Master your Data: How graphs change your view • 4:15 - 4:45: Real Time Recommendations with Graphs: How to tap into what your customers really want • 4:45 - 6:00: Reception & Networking 2
- 3. 3 Today’s Presenters David Mohr Director,Eastern Region Utpal Bhatt VP, Global Marketing Confidential – Neo Technology, Inc. David Fauth Field Engineer
- 4. High Business Valuein Data Relationships Data is increasing in volume… • New digital processes • More online transactions • New social networks • More devices Using Data Relationships unlocks value • Real-time recommendations • Fraud detection • Master data management • Network and IT operations • Identity and access management • Graph-based search … and is getting more connected Customers, products, processes, devices interact and relate to each other Early adopters became industry leaders
- 5. How You UnlockValue from Your Data Relationships • Need to store data relationships natively • Model your data as a network (graph) of data and relationships • Use relationship information in real- time to transform your business • Add new relationships on the fly to adapt to your changing business
- 6. Relational DBs Can’tHandle Relationships Well • Cannot model or store data and relationships without complexity • Performance degrades with number and levels of relationships, and database size • Query complexity grows with need for JOINs • Adding new types of data and relationships requires schema redesign, increasing time to market … making traditional databases inappropriate particularly when data relationships are valuable in real-time Slow development Poor performance Low scalability Hard to maintain
- 7. NoSQL Databases Don’tHandle Relationships • No data structures to model or store relationships • No query constructs to support data relationships • Relating data requires “JOIN logic” in the application • No ACID support for transactions … making NoSQL databases inappropriate when data relationships are valuable
- 8. Neo4j – Re-ImagineYour Data as a Graph Neo4j is an enterprise-grade graph database that enables you to: • Model and store your data as a graph • Query data relationships with ease and in real-time • Seamlessly evolve applications to support new requirements by adding new kinds of data and relationships Agile development High performance Vertical and horizontal scale Seamless evolution
- 9. CAR name: “Dan” born: May29, 1970 twitter: “@dan” name: “Ann” born: Dec 5, 1975 since: Jan 10, 2011 brand: “Volvo” model: “V70” Property Graph Model Components Nodes • The objects in the graph • Can have name-value properties • Can be labeled Relationships • Relate nodes by type and direction • Can have name-value properties LOVES LOVES LIVES WITH PERSON PERSON
- 10. The Whiteboard ModelIs the Physical Model
- 11. Value from DataRelationships Common Use Cases Internal Applications Master Data Management Network & IT Operations Fraud Detection Customer-Facing Applications Real-Time Recommendations Knowledge Graph Identity & Access Management
- 12. Real-World Neo4j BusinessBenefits New Competitiveness • New, unique functionality • New insights into data Better Software • Better code quality • Less complexity • More maintainable Using the right tool for the job has profound effects on your business User Success • Faster app performance • Better user experience • Improved user productivity Project Success • Faster time to market • Lower costs Neo4j creates a connected data imperative
- 13. “Forrester estimates thatover 25% of enterprises will be using graph databases by 2017” Neo4j Leads the Graph Database Revolution “Graph analysis is possibly the single most effective competitive differentiator for organizations pursuing data-driven operations and decisions after the design of data capture.” IT Market Clock for Database Management Systems, 2014 https://www.gartner.com/doc/2852717/it-market-clock-database-management TechRadar™: Enterprise DBMS, Q1 2014 http://www.forrester.com/TechRadar+Enterprise+DBMS+Q1+2014/fulltext/-/E-RES106801 Making Big Data Normal with Graph Analysis for the Masses, 2015 http://www.gartner.com/document/3100219 By the end of 2018, 70% of leading organizations will have one or more pilot or proof-of-concept efforts underway utilizing graph databases.
- 14. Introducing Neo4j The GraphDatabase Leader Product Overview
- 15. Neo4j – KeyProduct Features Native Graph Storage Ensures data consistency and performance Native Graph Processing Millions of hops per second, in real time “Whiteboard Friendly” Data Modeling Model data as it naturally occurs High Data Integrity Fully ACID transactions Powerful, Expressive Query Language Requires 10x to 100x less code than SQL Scalability and High Availability Vertical and horizontal scaling optimized for graphs Built-in ETL Seamless import from other databases Integration Drivers and APIs for popular languages MATCH (A)
- 16. Relational Versus GraphModels Relational Model Graph Model KNOWS ANDREAS TOBIAS MICA DELIA Person FriendPerson-Friend ANDREAS DELIA TOBIAS MICA
- 17. Cypher: Powerful andExpressive Query Language MATCH (:Person { name:“Dan”} ) -[:LOVES]-> (:Person { name:“Ann”} ) LOVES Dan Ann LABEL PROPERTY NODE NODE LABEL PROPERTY
- 18. MATCH (boss)-[:MANAGES*0..3]->(sub), (sub)-[:MANAGES*1..3]->(report) WHERE boss.name= “John Doe” RETURN sub.name AS Subordinate, count(report) AS Total Express Complex Queries Easily with Cypher Find all direct reports and how many people they manage, up to 3 levels down Cypher Query SQL Query
- 19. Neo4j Clustering Architecture Optimizedfor Speed & Availability at Scale 19 Performance Benefits • No network hops within queries • Real-time operations with fast and consistent response times • Cache sharding spreads cache across cluster for very large graphs Clustering Features • Master-slave replication with master re-election and failover • Each instance has its own local cache • Horizontal scaling & disaster recovery Load Balancer Neo4jNeo4jNeo4j
- 20. Getting Data intoNeo4j Cypher-Based “LOAD CSV” Capability • Transactional (ACID) writes • Initial and incremental loads of up to 10 million nodes and relationships Command-Line Bulk Loader neo4j-import • For initial database population • For loads with 10B+ records • Up to 1M records per second 4.58 million things and their relationships… Loads in 100 seconds!
- 21. Data Storage and BusinessRules Execution Data Mining and Aggregation Neo4j Fits into Your Enterprise Environment Application Graph Database Cluster Neo4j Neo4j Neo4j Ad Hoc Analysis Bulk Analytic Infrastructure Graph Compute Engine EDW … Data Scientist End User Databases Relational NoSQL Hadoop
- 22. MIGRATE ALL DATA MIGRATE GRAPH DATA DUPLICATE GRAPHDATA Non-graph data Graph data Graph dataAll data All data Relational Database Graph Database Application Application Application Three Ways to Load Data into Neo4j
- 23.
- 24. Users Love Neo4j “Wefound Neo4j to be literally thousands of times faster than our prior MySQL solution, with queries that require 10 to 100 times less code. Today, Neo4j provides eBay with functionality that was previously impossible.” Volker Pacher Senior Developer Horizontal Scaling “The ability to have flexible schema and horizontal scalability is key to our success with Neo4j.” - IT Director, G5000 Professional Services Firm Social Recommendations “Neo4j has allowed us to integrate personalized user experiences—based on our users’ social relationships— into both product and marketing.” - Craig Follett, CEO, Universe True Game Changer “Things that were impossible became possible.” - Markus Paaso, Developer, Sagire Software
- 25. Summary Only Neo4j Unlocksthe Value in Your Data Relationships Data is increasing in volume… • New digital processes • More online transactions • New social networks • More devices … and is getting more connected Customers, products, processes, devices interact and relate to each other
- 26. Neo Technology The Createrof Neo4j About Neo Technology & Getting Started with Neo4j
- 27. 2000 2003 20092010 2011 2013 2014 20152012 Neo4j: The Graph Database Leader GraphConnect, first conference for graph DBs Introduced first and only declarative query language for property graph Published O’Reilly book on Graph Databases $11M Series A from Fidelity, Sunstone and Conor $11M Series B from Fidelity, Sunstone and Conor Commercial Leadership First native graph DB in 24/7 production Invented property graph model Contributed first GA graph DB to open source $2.5M Seed Round from Sunstone and Conor Funding Extended graph data model to labeled property graph 150+ customers 50K+ monthly downloads 500+ graph DB events worldwide $20M Series C led by Creandum, with Dawn and existing investors Technical Leadership
- 28. The Largest GraphEcosystem 2,000,000+ with 50k additional per month Neo4j Downloads ~200 customers 50+ from Global 2000 100+ Technology and Services Partners 450+ annual events & 10k attendees Graph and Neo4j awareness and training 35,000+ Neo4j Meetup Members 30,000+ Online and Classroom Education Registrants
- 29. 100 Best inShow 2015 Gartner’s Magic Quadrant for Operational Database Management 2015 Industry Recognition Technology of the Year 2015, 2014 100 Companies that Matter the Most in Data 2015 Neo4j named most popular Graph Database, 2015 Neo4j declared “Champion”, 2015 “Most Popular and Widely Deployed Database” Winner of NOSQL/ Graph Database Technologies, 2-15
- 30. SOFTWARE FINANCIALSERVICE S RETAIL MEDIA& OTHER SOCIAL NETWORKS TELECOM HEALTHCA RE Neo4j Customer by Selected Verticals
- 31. Neo Technology –Overview Product • Neo4j - World’s leading graph database • Latest version – Neo4j 3.x • ~200 enterprise subscription customers including over 50 of the Global 2000 • 273 startups enrolled in Startup Program Company • Neo Technology, Creator of Neo4j • 125+ employees • HQ in Silicon Valley with office in London, Munich, Paris and Malmö • $45M in funding from Fidelity, Sunstone, Conor, Creandum & Dawn Capital 31
- 32. How Can YouGet Started with Neo4j • Hold a Graph workshop • Select a Pilot use case that will return value • Engage with Neo
- 33. Introducing Neo4j The GraphDatabase End of Presentation