Rahul Tenglikar, Regional Director, India at Neo4j shares insights on how graph technology can help in making your organisation secure and future ready
What is the difference between a graph database and a normal database?
A traditional relational database structures data in tables, rows or columns making it possible to establish links between two data points and gain insights about their relationship. Over the years, these traditional databases have powered software applications and proved to be helpful in gaining insights from predictable data. Such databases only model data as a set of tables and columns, carrying out complex joins and self-joins when the dataset becomes more inter-related. These queries have often been complicated to construct, and expensive as well as difficult to run in real time.
This is where graph databases come into play. Graph databases are appealing because they enable businesses to derive meaning out of the huge chunks of data that they deal with. The flexibility of a graph data structure allows one to add new nodes and relationships without jeopardizing the existing network or going through expensive data migration. Graph databases, with data relationships at their core, are extremely efficient when it comes to query performance, even for deep and complex queries.
One of the most significant differences between graph databases and traditional/relational databases is that the connections between nodes are directly linked, making it simple to relate data and follow connections. Relationships are stored at the individual record level in a graph database, whereas a relational database uses predefined structures.
Who are the beneficiaries of graph technology?
All organizations today collect huge amounts of data. Collecting this data is not enough to attain maximum advantage in competitive markets. Organizations need to mine this data in a way which enhances their decision making, supplemented with intelligent insights based on the data collected. Graph technology is what helps them unlock this potential of their data. Therefore, companies irrespective of their nature or industry can leverage graph technology and gain unparalleled advantage.
We already have graph technology being implemented by banking institutions to identify financial crimes, by governments to fight crime, prevent terrorism, improve fiscal responsibility, and provide transparency and also by telecom companies to manage increasingly complex network structures. These are just a few of the ways in which graph technology is being leveraged. The same can be applied across any industry.
Inherently, any data that involves three or four hops within its data set will become a perfect candidate for graph technology to add value.
How secure is graph data considering security is a big challenge these days?
With the ever-evolving technology landscape, security undoubtedly continues to remain a major challenge for organizations. Frauds, data breaches and ransomware attacks have become very sophisticated and the impact that they have on a company is not only difficult to manage but often long lasting. It impacts regular operations, company reputation, sales and ultimately the growth trajectory of the company.
Graph technology is a very evolved and intelligent way of dealing with such issues. Firstly, graph platforms like Neo4j suit the security function very well because the organization’s data is secured within one’s own environment without any intervention or handover to an external third-party vendor. Additionally, graph technology serves as a cybersecurity solution by helping detect breaches and enabling faster recovery in the event of an accident.
Neo4j graphs provide database-level security. Role-based access control enables organizations to create sensitive data rules and know that those rules will be applied across all Neo4j applications and uses.
What are the areas organizations need to be mindful of while deploying graph technology for cybersecurity?
Organizations today require a robust system in place to address the increasing security concerns. With restricted corporate networks becoming more prone to cyberattacks, the usual security framework is becoming irrelevant. Organizations need to understand that adopting a layered approach to security and using the latest cybersecurity tools is not enough. They need to be mindful and have an effective security posture which refers to the awareness of assets, processes to monitor and maintain security, and ability to detect, handle and recover from attacks.
For this, they must maintain a live representation of their network structure for analysis purposes. There should be an understanding of the most likely attack paths and a plan to combat the same. For organizations that already have some graph analytics in place, they should look at pushing their capabilities further. A connected data platform like ours can go beyond just supporting the basic functions and enable operational applications, such as real-time card ecommerce fraud detection, border control, and so on. It also comes with a low TCO (total cost of ownership) and gives you the ability to customize capabilities according to your organization’s needs.
Graph databases easily capture the complexity of IT infrastructure and security tools.Graph visualizations can then show the critical information needed to determine how to stop the attack, which could include blocking user accounts or access from specific IP address ranges. When a company faces a cyberattack, predicting the attackers’ next move is as simple as matching the latest attack with a node on the graph and seeing what happens next.
How is the product offered to the customers?
Neo4j has multiple offerings at different price points depending on different levels of usage. Aura free, our community edition, is a free version that small businesses and start-ups can use for small development projects, learning, experimentation, and prototyping. We also have Aura professional, which is available at a competitive cost and can be used by mid-tier companies who want to get started with Neo4j and explore its offerings. It helps with medium scale applications in advanced development or production environments. The AuraDB professional is used for large scale, mission-critical applications that require advanced security and round the clock support. Earlier this year, we also announced Neo4j Graph Data Science which is a comprehensive graph analytics workspace with new and enhanced capabilities built for data scientists. It is available as a fully managed cloud service called AuraDS.
What are you doing to market the products and develop evangelists? How are you supporting the developers?
In most organizations, developers are the first people who try our offerings, especially our community version which is free to use. Developers and data scientists are at the heart of Neo4j.They help us evangelize use cases of our products within their organizations. Most of the product enhancements too, usually, come as product feedback from our developers.
For the community, we encourage learning and experimenting with our offerings. We have tutorials, guides, a pool of resources – including blogs and videos – to help them understand the product comprehensively. We also organize meetups for them that serve as a platform to share ideas, experiences to learn and grow together.
Neo4j also organized the GraphSummit in Bangalore. The event offered new and exciting opportunities to meet and learn from Neo4j experts in the field of graph data science. Neo4j scientists also hosted workshops showcasing the development of knowledge in graphs by activation of Aura DB. With India having the largest community of graph data professionals, the Graph Summit also provided a platform for them to interact, network and share their graph stories with their peers.