Introduction

You can use API integrations to connect data other sources, such as databases, documents, applications, websites, and intranets. In this section, we will explain how you can model your data into a graph database, demonstrate how to create nodes, edges, and properties using the APIs. And provide some examples and best practices for writing efficient and reliable code.

Basic Concepts

• Data Connector: A data connector is an external process that extracts data from a source location and writes it into your Curiosity workspace. It runs outside of the workspace and interacts with it via available APIs.

• Data Model: A graph data model represents data as nodes with properties (entities) and edges (relationships). Graph databases are well suited for complex queries that involve multiple hops and filters across different types of data.

• Nodes: Nodes are the entities or objects in your dataset, such as people, products, events, etc. Nodes have labels that indicate their type, such as Person, Product, Event, etc. Nodes can also have properties that store additional information about them, such as name, age, price, date, etc.

• Edges: Edges are the relationships or connections between nodes. Edges have types that indicate their meaning, such as KNOWS, BUYS, ATTENDS, etc.