Implementing complex data access controls is easier than ever before.
For Neo4j 4.0, we put a great deal of emphasis on ways graph technology enhances security.
As application development changes, today’s graph database needs to enforce rigorous enterprise security rules while remaining easy to deploy and manage.
Protections like “row-level” security in a relational database are important, but it's not enough when using graphs. Graphs have meaningful structure and data, which requires a security system that understands that.
The data in a graph database is not the only thing that needs protection. The structure of the relationships and nodes in a graph are themselves information. Our security system takes that into account.
Neo4j 4.0’s new schema-based security makes it easy to enforce this level of protection, regardless of whether there are multiple on-premise graph databases or an enormous graph sharded across multiple cloud repositories around the world.
Identity and Access Control
Neo4j offers granular security down to individual objects and their properties, and control permission to traverse, read or write data based on node labels, relationship types or database and property names.
With a role-based access control approach, you can restrict access at any level of granularity, and these controls cascade downwards throughout the database.
In a graph structure, this greatly simplifies the task of assigning permissions.
Neo4j 4.0’s multi-database capabilities make it easier for organizations to adhere to privacy and security regulations.
For example, GDPR regulations require data for a particular country’s citizens must be physically stored in that country. With Neo4j 4.0, that is now possible without having to create a separate database for those citizens.
Building security into the database simplifies secure application development. Rather than tasking developers with security, developers write their applications against a scalable and security-conscious Neo4j 4.0 backend.
The modern application development process puts a premium on velocity, which is why ease-of-use and flexibility for developers have become as critical as performance for database platforms. One of the ways this is achieved is by avoiding the need for cumbersome data abstractions to translate between business needs and relational schemas. Graph databases are a canonical example of this, and Neo4j remains one of the pioneers of the category committed to bringing the benefits of graphs to a wide variety of customer types and use cases.”Stephen O’Grady, Principal Analyst at RedMonk
The unmatched scalability of Neo4j 4.0 lends itself to emerging AI and machine learning use cases, which require graphs to scale reliably across massive datasets to give learning applications context and to make AI more explainable. In addition, the ability to apply fine-grained security on nodes and relationships in a flexible way will have immediate impact across a broad range of use cases.”Michal Bachman, CEO of GraphAware
At albelli, we regularly deal with petabytes of data, and we are most excited about the new scalability features in Neo4j 4.0. The ability to horizontally scale with the new sharding and federation features, alongside Neo4j’s optimal scale-up architecture, enables us to grow our graph database without barriers. Neo4j factored our requirements into their latest release — a mark of a great vendor and a graph database designed for the future.”Josh Marcus, Chief Technology Officer at albelli