Identity and Access Management
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The document discusses how graph databases can be used to improve identity and access management (IAM) systems. Traditional IAM systems are based on rigid hierarchies and siloed data, but organizations are becoming more complex with interconnected relationships. Graph databases allow IAM data to be modeled as a graph, enabling querying of complex relationships in real-time. The document provides an example of how a telecom company improved their IAM system performance by moving it to a graph database. It also outlines how graph databases can be incorporated into existing IAM architectures and systems.
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Identity and Access Management
- 1. Identity & Access ManagementLEVERAGING CONNECTIONS IN DATA WITH GRAPH DATABASES Webinar, September 22, 2016
- 2. Alessandro Svensson Solutions @ Neo Technology Ryan Boyd Developer Relations @ Neo Technology
- 3. Agenda Intro to Graph Thinking Defining Identity & Access Management How IAM is evolving Use of graph databases in IAM Case studies - Adoption of Neo4j Demo Wrap up & Questions.
- 4. Intro to Graph Thinking
- 5. Databases have evolved in order to handle large networks of connected data
- 6. Databases have evolved in order to handle large networks of connected data
- 8. The internet is a graph Huge networks of connected data
- 10. This is data modelled as graph!
- 16. A Graph Is
- 18. and for the right reason at the right time,Who gets access to what, Identity & Access Management (IAM)
- 19. & Access ManagementIdentity Defining Identity
- 20. & Access ManagementIdentity The structure of organisations
- 21. Traditional IAM-systems 2) Underlying assumption that organisations are hierarchal 1) Static idea of Identity
- 26. 1) Identity is increasingly complex What’s happening in the world of IAM?
- 27. 2) Traditional hierarchies are being revised 1) Identity is increasingly complex What’s happening in the world of IAM?
- 28. 2) Traditional hierarchies are being revised 1) Identity is increasingly complex What’s happening in the world of IAM? 3) Access Management is more and more about the relationships between users, partners, customers, things and their different touchpoint within organisations and eco-systems
- 29. Emerging Complexity of Identity
- 30. Complexity of Digital Identities User identities Identity of Things Serial # Unique idPersonal Customer Partner Consumer Citizen
- 31. Device <-> Service Security End to EndIdentity of users Identity of things Applications and services Complexity of Digital Identities
- 32. Identity Relationship ManagementIdentity Access Management Applications and data Endpoints People Customers (millions) Partners and Suppliers Workforce (thousands) PCs Tablets On-premises Private Cloud Public Cloud Things (Tens of millions) WearablesPhones PCs Customers (millions) On-premises Applications and data Endpoints People
- 33. Identity Relationship ManagementIdentity Access Management Applications and data Endpoints People Customers (millions) Partners and Suppliers Workforce (thousands) PCs Tablets On-premises Private Cloud Public Cloud Things (Tens of millions) WearablesPhones PCs Customers (millions) On-premises Applications and data Endpoints People
- 34. Identity Relationship ManagementIdentity Access Management Applications and data Endpoints People Customers (millions) Partners and Suppliers Workforce (thousands) PCs Tablets On-premises Private Cloud Public Cloud Things (Tens of millions) WearablesPhones PCs Customers (millions) On-premises Applications and data Endpoints People
- 35. Access Management is traditionally designed with the underlying assumption that everything is hierarchal
- 36. Access Management is traditionally designed with the underlying assumption that everything is hierarchal
- 37. Rigid hierarchies have defined how we have built IAM-systems in the past
- 38. Representing your organisation as a graph, enables you to build stronger and more accurate IAM
- 39. Parent-Child relationships Ideal World Query complex relationships in real-time Real World
- 40. How Neo4j is used in IAM
- 41. 1. Build your IAM as a Graph 2. Augment your existing IAM with Neo4j Different ways of adopting Neo4j
- 42. Case Study
- 43. 43 Identity and Access Management Telenor Background • Oslo-based telcom provider, #1 in Nordic countries and #10 in world • Online, mission-critical, self-serve system lets users manage subscriptions and plans • Availability and responsiveness is critical to customer satisfaction Business Problem • Logins took minutes to retrieve relational access rights • Massive joins across millions of plans, customers, admins, groups • Nightly batch production required 9 hours and produced stale data Solution and Benefits • Shifted authentication from Sybase to Neo4j • Moved resource graph to Neo4j • Replaced batch process with real-time login response using most recent data • Mitigated customer retention risks
- 44. 44 Identity and Access Management Telenor Background • Oslo-based telcom provider, #1 in Nordic countries and #10 in world • Online, mission-critical, self-serve system lets users manage subscriptions and plans • Availability and responsiveness is critical to customer satisfaction Business Problem • Logins took minutes to retrieve relational access rights • Massive joins across millions of plans, customers, admins, groups • Nightly batch production required 9 hours and produced stale data Solution and Benefits • Shifted authentication from Sybase to Neo4j • Moved resource graph to Neo4j • Replaced batch process with real-time login response using most recent data • Mitigated customer retention risks
- 45. Case Study
- 46. Challenges with existing IAM: Partner • Employee ID • Partner ID • Digital credentials • Sales record • Job Performance Customer • Employee ID • Company ID • Digital credentials • Devices managed • Portal software • Maintenance Employee • Employee ID • Roles • Digital Identities • Digital credentials • Personal devices Device • Serial number • Digital credentials • Make & model • GPS location • IP-adress • Firmware • Maintenance Consumer • Full name • Date/place birth • Home adress • Eye & hair color • Height/weight • Email Adress Data will be separated in Silos
- 47. Partner • Employee ID • Partner ID • Digital credentials • Sales record • Job Performance Customer • Employee ID • Company ID • Digital credentials • Devices managed • Portal software • Maintenance Employee • Employee ID • Roles • Digital Identities • Digital credentials • Personal devices Device • Serial number • Digital credentials • Make & model • GPS location • IP-adress • Firmware • Maintenance Consumer • Full name • Date/place birth • Home adress • Eye & hair color • Height/weight • Email Adress Data will be separated in Silos Identity data will be very static Challenges with existing IAM:
- 48. Partner • Employee ID • Partner ID • Digital credentials • Sales record • Job Performance Customer • Employee ID • Company ID • Digital credentials • Devices managed • Portal software • Maintenance Employee • Employee ID • Roles • Digital Identities • Digital credentials • Personal devices Device • Serial number • Digital credentials • Make & model • GPS location • IP-adress • Firmware • Maintenance Consumer • Full name • Date/place birth • Home adress • Eye & hair color • Height/weight • Email Adress Data will be separated in Silos Identity data will be very static Based on a hierarchal representation of an organisation Challenges with existing IAM:
- 49. Partner • Employee ID • Partner ID • Digital credentials • Sales record • Job Performance Customer • Employee ID • Company ID • Digital credentials • Devices managed • Portal software • Maintenance Employee • Employee ID • Roles • Digital Identities • Digital credentials • Personal devices Device • Serial number • Digital credentials • Make & model • GPS location • IP-adress • Firmware • Maintenance Leverage Cross-Silo Relationships to drive new business value Name CuID Emp ID Partne r Emp ID Compa ny Y Emp ID GPS Loc GPS Loc Emp ID Dig Serial# GPS Loc GPS Loc Firmw are Serial# Consumer • Full name • Date/place birth • Home adress • Eye & hair color • Height/weight • Email Adress Relationship Layer How Can You Augment This with Graphs?
- 50. Partner • Employee ID • Partner ID • Digital credentials • Sales record • Job Performance Customer • Employee ID • Company ID • Digital credentials • Devices managed • Portal software • Maintenance Employee • Employee ID • Roles • Digital Identities • Digital credentials • Personal devices Device • Serial number • Digital credentials • Make & model • GPS location • IP-adress • Firmware • Maintenance Leverage Cross-Silo Relationships to drive new business value Name CuID Emp ID Partne r Emp ID Compa ny Y Emp ID GPS Loc GPS Loc Emp ID Dig Serial# GPS Loc GPS Loc Firmw are Serial# Consumer • Full name • Date/place birth • Home adress • Eye & hair color • Height/weight • Email Adress Relationship Layer How Can You Augment This with Graphs?
- 52. OpenAM Agent Service that user wants to use Login username passwords Host Architecture OpenAM Write Event AuthZ Plugin Authorize Service for User
- 53. Learn more about this case study, visit the Neo4j Youtube-channel or graphconnect.com
- 54. Ryan Boyd Developer Relations @ Neo Technology Neo4j DEMO
- 56. Government Commercial clients Who’s Using Neo4j? Institutions Local Governments Law Enforcement Military & Intelligence
- 57. Neo4j Adoption by Selected Verticals SOFTWARE FINANCIAL SERVICES RETAIL MEDIA & OTHER SOCIAL NETWORKS TELECOM HEALTHC ARE
- 60. “Graph analysis is possibly the single most effective competitive differentiator for organizations pursuing data-driven operations and decisions after the design of data capture. “By the end of 2018, 70% of leading organizations will have one or more pilot or proof-of-concept efforts underway utilizing graph databases.” Towards Graph Inevitability
- 61. “Forrester estimates that over 25% of enterprises will be using graph databases by 2017.” Towards Graph Inevitability
- 62. Valuable Resources! neo4j.com/developer neo4j.com/solutions neo4j.com/product Developers Solutions Product
- 64. Thank you!
Notas do Editor
- Hi, and welcome to this Neo4j-webinar on Identity & Access Management
- My name is Alessandro Svensson, and I work with Solutions at Neo Technology. Together with me today I have Ryan Boyd from our Developer Relations-team, and he’s going to provide us with some Neo4j and Cypher demonstrations around IAM, later on.
- So thank you for joining us. This is today’s agenda: We have a lot to cover today and we’re going start of with a short intro to graph thinking, and move on to defining IAM, and then talk a little about how IAM is evolving. We’re going to talk about the emerging use of graph databases in IAM, the adoption of Neo4j in this space. Then Ryan is going to demo Neo4j, and then we’ll wrap things up and leave time for some questions.
- Okay, so let’s begin with talking a little bit about Graphs and graph thinking. Some of you are probably familiar with this, but it doesn’t hurt to get into the world of graph thinking a little bit before we get into IAM. I think to understand what graphs are and where they come from…
- We have to consider the way databases have evolved in order to handle large networks of…
- …connected data.
- While the traditional relational databases are great for storing data that is heavily structured. That’s just not how data looks anymore.
- What we see is a huge explosion of connectivity and value being created within huge networks of connected data.
- Another way to put it, is to say, data structured as tables, columns and rows… is evolving…
- …to be stored and modelled in a way that the data is relating to itself. And this is what modeling data as graph is.
- A graph is connected data. Which essentially means – datapoints (or nodes as we call it) that have relationships with other datapoints.
- This could be a person, that has checking account with a bank.
- Or a hotel that has rooms, which have availability
- Or it could be people who know other people – who know other people.. who studied together, who work at the same place – who studied with other people, who works somewhere else… etc.
- This is EXACTLY how data appears in Neo4j. One of the benefits with this model is that it is extremely intuitive to understand, very easy to model. The interesting thing is what happens when you start to add more and more relationships to these graphs, and these things start to take off at scale…
- …and forming an extremely powerful foundation from which you can derive value through analysis, perform real-time queries to build extremely powerful applications and algorithms.
- Today we’re going to talk about graphs in Identity and Access Management. IAM is traditionally defined as the process of assuring “Who gets access to what, at the right time, and for the right reason”
- There are two major themes that affect IAM, and that is: • How you define Identity, and…
- …your perspective of the the structure of organisations.
- The penalties we see with traditional Identity and Access Management systems are that they 1) tend to have a very static and limited idea of what identity is. And 2) that there’s an underlying assumption that organisations are strictly hierarchal. And this have affected how we used to approach Access Management in the past.
- Ian Glazer at Gartner made a very elegant and simple explanation of how access management-processes works in a blogpost a couple of years ago. And I’d like to recap some of his major points, because it says a lot about the legacy that exists when you talk about IAM. 1. Traditionally, what happens is that when an individual is hired and put in an HR-system, an IAM-process gives that individual access to different resources and systems within an enterprise.
- 2. That’s what happens when someones ADDED to the organisation.
- 3. Similarly we see what happens when someone CHANGES jobs. In this particular scenario someone moves from costumer support to Inside Sales. That too, signals the IAM-processes to do something, by way of HR. In this case, remove someone from the Knowledge base and give them access to CRM.
- 4. And lastly someone LEAVES the organisation, and that signals the IAM-process to remove that individual from all access. Ian Glazer talks about how these are the three major traditional life-cycle triggers within IAM. And it works, it definitely fits a purpose, but it’s also a very linear process that doesn’t really mirror all the complexities of an enterprise in a digitized world.
- So there’s a lot of things happening in the world of IAM, and we’d like to go through some of what we feel are the most important ones. First, the definition of identity is getting increasingly complex.
- Second, the view of a world that is strictly hierarchal is being revised.
- Third, Access Management is more and more about connections, and the relationships between users, partners, customers, things, and different touchpoint within organisations and eco systems.
- Let’s talk about the emerging complexity of Identity.
- In a digitized world, everything has an identity. When you think about digital identity you often think about passwords and user names or at least some characteristics that has to do with your person. While that is, of course accurate, it’s also a somewhat limited view of what identity can be. Identity is often a COLLECTION of attributes. A person’s identity will differ, depending on the role that the person has at the moment. For example, an identity can be a personal identity. At the same time you might have consumer identity, a customer identity, a partner identity if you’re an enterprise supplier or a contractor, or simply a citizen identity. All of which collects a richness of attributes within themselves. Similarly, things also have identities. And here we talk about identity in terms of Serial# and Unique IDs. So, your phone will have an identity, a washing machine has an identity and so on.
- The interesting thing is when you start collecting and connecting these identities in networks. Things have links to humans, and humans will have links to things, and so. And all of this will, of course, be reflected in your applications and services. In that regard, identities are becoming almost the heart of your applications and services. Not only from a personalized user experience point of view, but also, linking your devices and apps to the right identities, also becomes a matter of security and matter of mitigating vulnerability. So, identity is becoming extremely complex, and this new paradigm is, of course, changing how we should approach Identity and Access Management.
- So let’s see what’s happening in the the world of IAM. Access Management used to be pretty straight forward. And the IAM-processes used to represent a pretty simplistic world of what access meant. People accessed applications hosted on-premiss, through specific devices. And in a scenario like this one, access management isn’t really that complicated. Today, this is simply not a reality. As we discussed previously, 1) people take on several different roles, 2) and (even if you don’t think about it) they will be connected and require secure access to millions of things, they will use different types of devices with different types of dependencies, 3) and all of these individuals and roles will expect to access and use services and applications in a very granular and personalized way. So all of this is, of course, highly interconnected. And all these relationships have tremendous value. and your IAM-processes has an enormously important role to play, and from many different perspectives. …And I think this picture show you that what’s emerging are the incredibly rich data-relationships between people and things, and the different personas of people and things, and the job of IAM is going to be to use these relationships to manage who gets access to what — whether it is about accessing data coming from an IOT device or whether it’s about access to control devices remotely, or whether a device should have access to a cloud API or whether a person could share information with another person, etc… In all these different scenarios you can provide a richer experience by leveraging these relationships between all these people and things and be able to play out these different scenarios and ask those questions in real-time. This is what the world looks like, and it’s scaling rapidly. We’re going to reach an environment where we’ll see connected devices and people by the billions, so just imagine how many data-relationships that have to be in place to make sense of all this, knowing that when devices are being connected, if they’re not properly secured, it’s a huge risk from a privacy and cyber security point of view. So data-relationships are going to be a key part of the future when we build IAM-systems and when managing digital identity. And, an enterprise who doesn’t appreciate and understand the full complexity of who the customers are in an environment like this, will probably start faltering quite quickly. So it’s very exciting times for IAM, and especially for graph databases within IAM. I think how we securely manage these billions of relationships between users and things, and collaborators, employees, customers and consumers is going to be one of the epic undertakings of the future.
- …And I think this picture show you that what’s emerging are the incredibly rich data-relationships between people and things, and the different personas of people and things, and the job of IAM is going to be to use these relationships to manage who gets access to what — whether it is about accessing data coming from an IOT device or whether it’s about access to control devices remotely, or whether a device should have access to a cloud API or whether a person could share information with another person, etc… In all these different scenarios you can provide a richer experience by leveraging these relationships between all these people and things and be able to play out these different scenarios and ask those questions in real-time. This is what the world looks like, and it’s scaling rapidly. We’re going to reach an environment where we’ll see connected devices and people by the billions, so just imagine how many data-relationships that have to be in place to make sense of all this, knowing that when devices are being connected, if they’re not properly secured, it’s a huge risk from a privacy and cyber security point of view. So data-relationships are going to be a key part of the future when we build IAM-systems and when managing digital identity. And, an enterprise who doesn’t appreciate and understand the full complexity of who the customers are in an environment like this, will probably start faltering quite quickly. So it’s very exciting times for IAM, and especially for graph databases within IAM. I think how we securely manage these billions of relationships between users and things, and collaborators, employees, customers and consumers is going to be one of the epic undertakings of the future.
- So it’s very exciting times for IAM, and especially for graph databases within IAM. I think how we securely manage these billions of relationships between users and things, and collaborators, employees, customers and consumers is going to be one of the epic undertakings of the future.
- Another aspect that we wanted to highlight, is the legacy that many IAM-systems and processes face, which is that the technology that has been used traditionally within IAM, is based on the underlying assumption…
- …that everything is strictly hierarchal.
- They way we handle identity HAS TO become more intelligent, more active and more adaptive. And these static structures and hierarchies simply don’t do the trick. The rigid hierarchy that we normally associate with organisations and companies, that’s just not an accurate view of how the world works given the increasingly collaborative nature of business and organisations. The interactions and relationships that take place within a business are far more complicated than this.
- …the fact is that reality looks more like a graph. Graphs are the best way of representing data-relationships. It’s impossible to represent the richness of semantics, how different roles interrelate and of how their access ought to be managed, using a rigid hierarchy. This is one of the reasons why traditional IAM-systems don’t model relationships well.
- There’s also a purely technical aspect of this. The strict hierarchy represents, from a technical point of view, basically what you can achieve with classic “Parent-child” type of relationships… which kind off force you to build hierarchies in the shape of tree structures. And sure, from an access management-point of view, this would be an ideal world. The problem, again, is that the real world doesn’t look like this. The real world is not properly represented by a rigid structure. It’s dynamic, it’s interconnected, and constantly evolving, which means that if you want to force a structure that is not a tree, into a tree-structure, you’re going to be very vulnerable. And that’s another reason why a shift to graphs within Identity and Access Management is so important. Because graphs have the ability to represent, model and store data-relationships in a way that is closer to reality, and then query this data in real-time.
- So let’s look at some examples how Neo4j is used in IAM.
- We see two major trends trends in which Neo4j is being adopted. The first is to simply build you IAM-system as a graph from scratch. Augment your existing IAM with Neo4j.
- Let’s look at a couple of case studies. Telenor is an example of a company that has built an entire Identity and Access Management Repository using Neo4j.
- Telenor is a Telecommunications provider. It’s #1 in the Nordic Countries and #10 in the world. So it’s a huge company, with thousands of employees and millions of customers. Telenor as built a access management-tool around Neo4j. As Telco-provider you have millions of customers, with different subscriptions, configurations, data-plans, devices etc. In that regard it’s a pretty complicated business. And most of these customers are enterprises themselves, where Telenor provides their employees with phones and subscription plans. And when Telenor makes a deal with these Enterprises, like a Walt Dinsey Company for example, what happens is that Telenor authorize access to the Telenor systems to certain administrators at these different companies. So, when you need a phone as an employee, you don’t have to deal with Telenor directly, you deal with your own local help desk or IT-department. And enterprises themselves, as we’ve learned, are very complex. There are sub-divisions, multiple business units, different groups and projects, different employee types. And these administrator’s are often only granted permission to administrate parts of these organisations. And as Telenor, if you want a 360° view of an enterprise customer, in order to provide efficient customer support, but also to enjoy up-sell and cross-sell opportunities, this becomes almost impossible to achieve without graphs. The fact is that the system they replaced was a system based on a relational database structure, with massive joins across millions of plans, customers, admins etc. And it required 9 hours every night just for the batch process, and it produced very stale data. So now with Neo4j they can enjoy real-time login response times using the most recent data, which significantly has led to mitigated customer retention risks along with other benefits. So that’s an example of a use case and its benefits, where a company has built something around Neo4j from scratch.
- The fact is that the system they replaced was a system based on a relational database structure, with massive joins across millions of plans, customers, admins etc. And it required 9 hours every night just for the batch process, and it produced very stale data. So now with Neo4j they can enjoy real-time login response times using the most recent data, which significantly has led to mitigated customer retention risks along with other benefits. So that’s an example of a use case and its benefits, where a company has built something around Neo4j from scratch.
- Another case study I want to show you is ForgeRock, who are doing very exiting stuff with graphs within IAM. And this is about how you can augment existing systems using graphs.
- Let’s recap a bit. We’ve talked about some of the challenges with existing IAM, and one of them is that identity data will often be separated into different Silos…
- …and that this data often will be very static.
- And finally that we often see that technical legacy, is based on the strictly hierarchal representation of an organisation, which ins’t accurate.
- What Forgerock is doing is that they use all the different kinds of data sources that exists within an organisation, and bring all these different data pieces in and reconcile them, and make sense of them in what they call a Relationship layer. And then pull that enriched data together so you can provision new accounts, new entitlements, different attributes, pulling that data back into your traditional enterprise identity management. And what they do is that they take different key pieces of information, not all the data, but the pieces that you need, and then weave together relationships between those and that’s where the graphs comes in, and that’s what they’ve built with Neo4j. So that they get this new sort of cross vertical, or cross-silo set of relationships, that provide a whole new set of insight, on top of existing systems. So you start to think about this in terms of your customer scenario where you’ve got a large enterprise of different lines of business, users who register with different types of account names across those lines, and you want to have a 360° view of who that customer is, and what kind of experience they had when they bought a product or subscribed to an online-service, when they visited your physical store, what kind of experience they’ve had when they interacted with your customer support etc — being able to take some of those key pieces of information and pull them up into a relationship layer and then extract value about who the customer is, what they’re looking for what they’re experiencing. You can also think about this in an enterprise scenario where you have your internal employees and contractors who are responsible for your day-to-day, and to keep your customer facing processes up and running efficiently. The relationship layer enables you to understand risk profiles better, to mitigate insider threats, whether intentional or unintentional. So the idea here is that when we live in a world where enriched accurate identity is becoming increasingly important when it comes to access, the point is that all the relationships that you can build between these entities will add this whole new level of value across your organisation.
- You can also think about this in an enterprise scenario where you have your internal employees and contractors who are responsible for your day-to-day, and to keep your customer facing processes up and running efficiently. The relationship layer enables you to understand risk profiles better, to mitigate insider threats, whether intentional or unintentional. So the idea here is that when we live in a world where enriched accurate identity is becoming increasingly important when it comes to access, the point is that all the relationships that you can build between these entities will add this whole new level of value across your organisation.
- Forgerock uses Neo4j in a couple of different ways. In this scenarion they use product called OpenIDM. OpenIDM has a tool that extracts key data from these different data-sources, as in the previous example, and reconcile this in what they called the relationship layer. And the way this works is that they’ve taken their scripted REST connector capability and they’ve built 1) a connector that talks to Neo4j 2) Then they use that connector along with the rules and mappings that goes along with it, to inject a series of nodes that are people based, and a series of nodes that are device based and then build relationships between them in Neo4j, before they pull it back into the traditional IAM. So that’s a way of augmenting existing systems with the use of graphs.
- Another way they use Neo4j is within their system OpenAM, which is a access management tool. This is a small sketch from a demo that Forgerock presented at GraphConnect last year, but I think it does a good job explaining the basic idea. What OpenAM does is that it restricts access and forces authentication when accessing different services. 1) OpenAM has an authorization plug in, that talks with the Neo4j database. 2) At the same time the openAM product is protecting the actual service that this particular individual wants to access. So the openAM agent sits there to intercept all the requests to make sure the user has the appropriate authentication. The idea is to restrict access into services, and the reason why they use a graph database is the complexity around identity and access, for all the reasons we discussed previously. And this is another example of how neo4j would fit in in an architecture, to augment existing systems.
- If you want more information about this particular case study, I really encourage you to check out Forgerocks presentation from GraphConnect in San Francisco last year. It’s available on the Neo4j Youtube Channel and at GraphConnect.com
- I’m going to hand over to Ryan Boyd, who’s going to walk you through some different IAM-scenarios in Neo4j. Please hang around for questions after and we’ll try to get to as many questions as possible. So, over to you Ryan.
- Summing up, we would like to give you an overview of who’s using Neo4j.
- And we have a solid adoption from everything from government data-operations, to institutions like the world economic forum, ICIJ And of course many commercial clients, in the Fortune 100’s. Like Walmart, eBay, Linkedin, Cisco etc.
- “Neo4j is the most popular graph database around, so we have a privileged view on many use cases and usage of graph databases. Neo4j is used in verticals as diverse as Software, Financial Services Retail, etc… across a wide range of use cases.”
- The Latest DB-Engine Ranking of Graph Databases, shows our popularity. Where we’re placed at number 1, september 2016.
- So graphs really are everywhere! As we like to put it — We’re moving towards a graph inevitability.
- Gartner talks about, graphs being the single most effective competitive differentiatior for data-driven operations today. And they predict that by the end of 2018, 70% of leading organizations will have at least on or more pilot or POC underway.
- Forrester goes so far as to say that 25% of enterprises will be using graph databases by next year even.
- I also want to give a shout out for som valuable resources for those of you who want to learn more. If you’re a developer, please visit our developers page If you’re interested in case studies and solutions, there’s a lot interesting use cases and case studies at our solutions web page. And if you want to learn more about the product and Neo4j, please visit our product page.
- Lastly, If you are in Bay Area around October 13, don’t forget register for GraphConnect, which is our yearly event in San Fransisco. There you you can sign up for training, listen to customers sharing their graph-projects, meet our Neo engineers and senior staff. It’s a lot of fun, and I strongly recommend it if you’re in town. Visit graphconnect.com for more information on that.
- Thank you for participating in this webinar. Thank you Ryan for demonstrating a bit of Cypher and Neo4j for us. I hope is was useful. Reach out to us if you have any questions. And I hope to see you again soon.