Getting Your Data Graph-Ready After deciding on the technology and the key operational and logistical questions you want to answer with graph, your next step is to build a graph data model.

Historians are electronic data recording products that are typically used for trend style data. Trend data is comprised of measurement samples over a period of time. Prior to automation of this data ...

A graph database is a dynamic database management system uniquely structured to manage complex and interconnected data. Unlike traditional databases organized in rows and columns, graph databases ...

Graph data modeling requires a different paradigm than modeling with Relational or other NoSQL databases. InfoQ spoke with Jim Webber and Ian Robinson about data modeling with Graph databases.

Key-value, document-oriented, column family, graph, relational… Today we seem to have as many kinds of databases as there are kinds of data. While this may make choosing a database harder, it ...

Preparing the data for React-vis To start, I’ve bootstrapped a React project with create-react-app and added a few dependencies: react-vis, d3-fetch to help pull in the CSV data, and moment to ...

The "Graph Item Type" does not default to "AREA", so be sure to select that for a traditional graph that looks like a rolling hill of data. It's safe to leave "Consolidation Function" to AVERAGE, and ...

AWS, Google, Neo4j, Oracle. These were just some of the vendors represented in the W3C workshop on web standardization for graph data, and what transcribed is bound to boost adoption of the ...

The Graph is an indexing protocol for Web3 applications that organizes blockchain data to make it easily accessible with GraphQL.

Available starting today, Neo4j Aura Graph Analytics is said to work with any kind of data source, including Oracle, Microsoft SQL, Databricks, Google BigQuery, Snowflake and Microsoft OneLake.