Graph databases are NoSQL based database models which are based on relationships between entities. This model allows low latency operations even as fast as constant time as compared to other traditional SQL database models.
Graph databases are based on a relation-centric model which have index-free adjacency, in short, an explicit graph structure. Unlike traditional SQL table-based models where data is organized in rows/tables, a graph database has nodes or entities connected to each other based on the relationship between them. Multi-model databases support the unique graph use cases.
The benefits of a graph database
According to research published in the International Journal of Electrical and Computer Engineering, graph databases offer the fastest response to a query. This is because traditional Relational Database Model completes operations via multi-level join operations on tables. In contrast, a graph database runs a traversal, running from one node to another until target information is identified. Sub-graphs are identified in every step and irrelevant information remains untouched. This architecture allows it to perform operations in real-time which is becoming a necessity in the modern environment where data is constantly flooding in and needs to be processed immediately for applications such as Internet of Things (IoT), social media and business analytics for eCommerce etc.
Graph databases require much less code, which can mean fewer bugs, hence saving time in correcting query errors and more time for IT to work on other, more pressing problems.
Macrometa offers a GraphDB model, as part of the Global Data Mesh, with a latencies less <50ms. for real-life use cases like fraud detection and can be applied to ready-to-go industry solutions or customized offerings.