Data modeling (or schema design) is in fact more important when dealing with NoSQL than it was with relational databases. We just need a different kind of data modeling than in the past.

Titled "X-Stor: A Cloud-native NoSQL Database Service with Multi-model Support", the paper reveals Tencent used graph databases to store info about user relationships for its social networks, wide ...

The evolving landscape of NoSQL databases and NoSQL database management systems (NoSQL DBMS) has everything to do with Big Data analytics.

Graph databases facilitate discovery and analysis closely connected facts. This post is one of a series that introduces the fundamentals of NOSQL databases, and their role in Big Data Analytics.

Before looking into a graph database provider, make sure your intended use works well with the graph model. This means any application that can benefit from using graphs to manage data relationships.

Graph databases, such as Neo4j, ... MongoDB is far and away the most popular of the NoSQL databases. Its document data model gives developers great flexibility, ...

A graph database is a dynamic database management system uniquely structured to manage complex and interconnected data.

NoSQL databases are specialized to store different types of data like Key Value, Documents, Column Family, Time Series, Graph, and IoT data. Pascal Desmarets talks about how to perform data ...

Graph databases—like other NoSQL databases—typically use their own custom query methodology instead of SQL. One commonly used graph query language is Cypher , originally developed for the ...

Instead of storing data in rows/columns or documents, graph databases use the concept of nodes (for individual entities, such as a person or a thing) and edges that connect that node to other nodes. .