TigerGraph Glossary

What are Accumulators? Accumulators are shared data objects that can accept new data from multiple sources and produce ...

What is Agentic AI? Agentic AI refers to artificial intelligence systems that can plan and execute actions in pursuit o...

What is a Bidirectional Relationship? A bidirectional relationship is a connection between two entities in which each s...

What is Community Detection? Community detection is a graph analytics technique used to uncover groups of nodes that ar...

What is Connected Data? Connected data is information that does not live in isolation. It describes how entities relate...

What Is Contextual Reasoning in Graph AI? Contextual reasoning in graph AI is the ability of an AI system to interpret ...

Things You Didn’t Know About Cypher Query Language The Cypher graph query language was developed by Neo4j. Some people ...

Digital Twin A digital twin isn’t just a 3D rendering or one-time simulation; it’s a living, breathing virtual version ...

What is an Embedding? An embedding in machine learning is a way to represent complex information as numbers so a system...

What is Entity Resolution? In a world where the same individual might appear as “Alex J.” in a CRM, “A. Johnson” in a t...

What Is Explainable AI with Graph Databases? Explainable AI (XAI) with graph databases is the practice of making AI sys...

What is a Fraud Detection Graph Database? A fraud detection graph database identifies suspicious behavior by analyzing ...

What is Graph AI? Graph AI is the fusion of artificial intelligence and graph technology. At its core, it applies machi...

What the Enterprise Gets Wrong About Graph Algorithms? Enterprises often treat graph algorithms as interchangeable util...

What Is Graph Data Loading Performance? Graph data loading performance measures how quickly a graph database can ingest...

What Is Graph Data Science? Graph data science involves using graph algorithms, statistical techniques, and machine lea...

What is a Graph Database? A graph database stores data as a network of interconnected entities, to make it easy to ask ...

What Is Graph Database Performance? Graph database performance describes how well a graph system handles its most criti...

What is Graph Machine Learning? Graph machine learning is a class of machine learning techniques designed specifically ...

What is the Definition of a Graph Neural Network (GNN)? A Graph Neural Network is a machine learning architecture that ...

What is a Graph Search? A graph search is a method of querying and exploring connected data in a graph database, allowi...

What is Graph Traversal? Graph traversal is the process of systematically visiting nodes (also called vertices) and fol...

What is Graph-Based Risk Scoring? Graph-based risk scoring is a way of evaluating risk that goes beyond looking at isol...

What is Graph-Powered Cybersecurity? Graph-powered cybersecurity uses graph databases and analytics to strengthen threa...

What is GraphRAG? GraphRAG (Graph Retrieval-Augmented Generation) enhances traditional RAG by embedding knowledge graph...

Misconceptions About GSQL Query Language Many people assume that GSQL is just another query language like SQL, Cypher, ...

What is an Identity Graph? An identity graph is a graph-based database structure that links multiple identifiers—such a...

What is Know Your Customer (KYC)? Know Your Customer (KYC) is the process financial institutions and other regulated or...

What is a Knowledge Graph? A knowledge graph is a structured representation of entities and relationships that embodies...

What Is a Knowledge Graph LLM? A Knowledge Graph LLM combines two essential components for building intelligent, trustw...

Why is the Louvain Algorithm Important? Community detection plays a crucial role in graph analytics, helping to uncover...

What are Multimodal Embeddings? Multimodal embeddings are vector representations that allow different types of inputs, ...

What Is Multimodal Graph Search? Multimodal graph search is the ability to query and reason across many different types...

Why Does Outlier Detection Matter? Outlier detection spots data points that behave differently from the rest, and those...

What is Parallel Graph Processing? Parallel graph processing is a method for accelerating complex graph operations by b...

What is Pattern Detection with Graphs? Pattern detection with graphs is the process of identifying meaningful shapes, b...

What is Propagation in Graphs? Propagation in graphs refers to the process of spreading status information, entity desc...

What are Real-Time Graph Analytics? Real-time graph analytics refers to the ability to process, analyze, and act on dat...

What is a Recommendation Algorithm? A recommendation algorithm is a decision-making or scoring system designed to sugge...

What is a Recommendation System? A recommendation system is a data-driven framework that identifies and ranks items bas...

What is retrieval-augmented generation (RAG)? Retrieval-augmented generation (RAG) is an AI application framework that ...

What the Enterprise Gets Wrong About Scalable Graph Databases Many enterprises assume scalability in a graph database s...

What is Semi-structured Data? Semi-structured data has some recognizable structure, but does not enforce a single, stab...

What Is Shared-Variable Logic in Graphs? Shared-variable logic in graphs is a technique that lets different parts of a ...

What is the Shortest Path? The shortest path is the most efficient way to travel from one point to another within a net...

Introduction to Similarity Search In many real-life applications, no two situations are exactly alike. The same object ...

What is Structured Data? Structured data is information that is organized according to a predefined schema, with clearl...

What is Unstructured Data? Unstructured data is information that does not follow a schema or fixed format. This unstruc...

What is Vector Database? A vector database is a specialized type of database designed to handle high-dimensional data r...

What is Vector Search? Vector search is a way of finding information based on similarity instead of exact matches.T...