Transforming the future of data with graph databases



The data management landscape is undergoing a serious transformation. While traditional relational databases have been the “go-to” data storage tool for some time, their limitations in handling complex, interconnected data have become clear. As the volume and complexity of data continues to increase, organizations are looking for more efficient and agile solutions to extract meaningful insights.

This is where graph databases and NoSQL come into play. Unlike relational databases, which work particularly well with structured data, graph databases are designed to model and store data as interconnected nodes and relationships. Graph databases focus on the relationships within the data and, more importantly, can reveal relationships you might not have known existed. NoSQL also works to think outside the traditional “data box” and enables the storage and querying of data outside the traditional structure found in relational databases. Compared to traditional solutions, these fundamentally different approaches offer significant advantages when dealing with complex queries that span multiple data domains.

Alan Jacobson

Chief Data & Analytics Officer at Alteryx.

Solving complex queries

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