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AI glossary

Vector Database

A vector database is a type of database built to store embeddings and quickly find information by meaning rather than by exact keyword matches.

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In this guide

  1. 1What Vector Database means
  2. 2Why Vector Database matters

What Vector Database means

An embedding turns text into numbers that represent meaning. A vector database is built specifically to store huge numbers of these embeddings and search them fast, returning the items closest in meaning to a query.

Imagine a library where books are shelved by topic and idea rather than alphabetically. Ask for something about "saving money," and it instantly hands you nearby books on budgeting and frugality - that is how a vector database retrieves content.

Why Vector Database matters

Vector databases are a core piece of AI tools that search your own content, such as RAG-based assistants. Knowing the term helps you understand how those tools are built.

Vector databases make search-by-meaning fast and scalable
They are a key building block of RAG systems
They power knowledge assistants that use your own documents
Many no-code AI tools include one behind the scenes

Frequently asked questions

Often not. Many no-code AI tools include vector storage built in, so you can create a chatbot trained on your documents without managing a database directly.

More AI terms

AI OrchestrationCoordinating multiple AI models, tools, and steps so they work together as one smooth system.Structured OutputAI responses returned in a fixed, organized format so other software can use them reliably.AI ModelThe trained program at the core of an AI tool that takes input and produces an output.PromptThe instruction or question you give an AI to tell it what you want it to do.Prompt EngineeringThe skill of writing and refining prompts to get accurate, useful results from AI tools.System PromptA behind-the-scenes instruction that sets an AI's role, tone, and rules for an entire conversation.

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