7 Powerful Databases Python Developers Should Know 10:25 am October 8, 2024 By Julian Horsey As a Python developer, your choice of database can greatly influence your project’s success.

AnzoGraph is a fast, horizontally scalable, OLAP graph database that brings a wealth of analytics capabilities to large graphs ...

Graph data science is when you want to answer questions, not just with your data, but with the connections between your data points — that’s the 30-second explanation, according to Alicia Frame.

Graph databases, which explicitly express the connections between nodes, are more efficient at the analysis of networks (computer, human, geographic, or otherwise) than relational databases. That ...

Integration of Python for data science, graph processing for NoSQL-like functionality, and it runs on Linux as well as Windows. At almost 30 years of age, Microsoft's flagship database has learned ...

Graph databases power data journalism on the biggest information leak ever.

Graph database developer Neo4j Inc. is upping its machine learning game today with a new release of Neo4j for Graph Data Science framework that leverages deep learning and graph convolutional ...

Graph database startup Neo4j raised $320 million at an over $2 billion valuation, highlighting the value of graph databases.

Neo4j is the biggest, oldest, and most successful graph database company in the world. Its eponymous database is relied upon by thousands of organizations to store and expose data in a graph manner, ...

Companies that want to use powerful graph algorithms to explore hidden connections in their data may want to check out TigerGraph, which today unveiled a pair of cloud-based offerings designed to ...