Extra tags: Graph
In today's digital world, data holds a key position and is regarded as one of an organisation’s most valuable assets. It's no longer just about collecting data and where you store it. Just as important is how you extract useful insights and information buried inside it.
These insights help companies in making well-informed decisions, paving the way for future growth and mitigating future issues. Machine Learning, a form of AI is on the rise, and companies with a lot of data have realised the value of extracting intelligence from it. All of this has highlighted the significance of Graph Databases.
Relationships and connections between data elements are captured in graphs. These relationships and connections can be employed in data analysis. Because graphs make it easier to investigate such relationships and generate new conclusions, they are becoming increasingly significant.
Unlike relational databases, graph databases can work with a large number of connected points of data and explore their relationships. Graph databases, rather than tables and columns, store and display data in graph structures, allowing for the easy and quick retrieval of complex hierarchical connections that are difficult to model and expensive to query in relational systems.
According to IDC, 30% of A2000 companies will employ graph databases by 2025, recognising the technology's use in a rising number of use cases involving relationship, influence, path, and pattern analysis.
This could not have come at a better time to begin utilising the technology, given the tremendous issues that today's developers and data practitioners confront, such as:
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A critical need for advanced analytics to support company strategy
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Morasses of siloed data, susceptible to growing regulations
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Digital projects hindered or stalled
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Pressure to deliver a better client experience
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Complex landscapes of systems that need to be rationalised ASAP
Given these combined business and technical challenges, you need a database solution that allows you to make rapid progress on mission-critical activities.
Neo4j AuraDB is a fast, reliable, scalable and completely automated cloud graph database as a service that enables developers to focus on their strengths – creating rich, data-driven applications – rather than wasting time managing databases. AuraDB now enables quick searches for real-time analytics and insights in a cloud-native environment, bringing the power of data relationships to the cloud.
Features of Neo4j AuraDB
There are numerous reasons why you should choose Neo4j to build your graph applications in the cloud:
Fast
With Neo4j AuraDB Enterprise, more data implies more value. Real-time insights come from quick queries across billions of nodes. Speed and agility go hand in hand with Neo4j. Relational schemas are inflexible, and updating them is inconvenient. But with Neo4j, you can change the data model at any time with a graph schema, allowing it to adapt to your changing needs.
Effortless
Neo4j AuraDB Enterprise is cloud-ready and managed by graph database professionals, allowing you to focus on what you do best: your application and strategy. Neo4j takes care of the rest.
Secure
Neo4j AuraDB Enterprise allows you to apply security to nodes and relationships in the graph in a variety of ways. Neo4j AuraDB Enterprise guarantees data privacy and eases the burden on developers by providing role-based access control at the schema level.
Not only that, this technology has enabled an increasing number of companies to employ graph databases for a variety of purposes, including fraud detection, real-time recommendation engines, master data management, network and IT operations, and so on. That's exactly what Neo4j can do for you, plus a lot more!
With this cloud-native graph database platform, building your application and innovating with your data can be your primary focus. Neo4j AuraDB Enterprise takes care of everything else. Click here to learn more.