Current enterprise data architectures include NoSQL databases co-existing with RDBMS. In this article, author discusses a solution for managing NoSQL & relational data using unified data modeling.

NoSQL databases are designed to store different types of data like Key Value, Documents, Time Series, Graph & IoT. Pascal Desmarets talks about how to do data modeling when using NoSQL databases.

An example of a popular graph database system is Neo4j. Another Choice: The Multi-Model DBMS Yet another choice in the NoSQL market is the multi-model DBMS. A growing number of vendors have delivered ...

Hackolade, a Belgium-based provider of data modeling software for NoSQL and multi-model databases, has introduced a data modeling software tool for the Couchbase NoSQL database community. With this ...

NoSQL is engineered for real-time big data, but it’s operational rather than analytical. Using NoSQL together with Hadoop is the answer for real-time big data, Couchbase CEO Wiederhold told eWEEK.

Certain types of data fit well with the graph data model, especially where navigation of multi-level relationships becomes crucial. The price paid for this is complexity in programming.

NoSQL and in-memory database technology is an evolution based on technology originally developed in the 1960s and 1970s. So, the supplier in question can’t claim what they’re doing is ...

Data Modeling For an in-depth guide to NoSQL data modeling techniques, read this article at the Highly Scalable Blog. Engine Comparison ...

1. Generic data model NoSQL analytics systems must possess a data model generic enough to abstract over the differences between common NoSQL data models.

There is a key reason that companies are increasingly turning to enterprise solutions such as Couchbase Inc. for a combined relational and NoSQL database model. It’s because data is on the move.