What is vector database? Why is it used?

Question

Anubhav Kumar · Answer

A vector database is a specialized type of database designed to store, index, and search
vector embeddings—numerical representations of text, images, audio, video, or any kind of data.
What is a Vector?
A vector in AI/ML is a list of numbers (e.g., 768-dimensional, 1536-dimensional) that represents the meaning or features of data.
Examples:
Text: “Laptop bag” → [0.24, -0.11, 0.89, ...]Image: A car photo → [0.72, 0.04, -0.33, ...]
These vectors are generated by models like:
OpenAI embeddingsBERTCLIPSentence TransformersCohere embeddings
What is a Vector Database?
A vector database is a database optimized to:
Store vector embeddingsPerform similarity search (find nearest vectors)Scale to millions or billions of embeddingsProvide fast retrieval using specialized indexing (HNSW, IVF, PQ, FAISS-like techniques)
Popular vector DBs:
PineconeWeaviateMilvusChromaQdrantElasticsearch (vector search mode)
Why Is a Vector Database Used?
1. Semantic Search
Traditional keyword search fails if words differ.
Vector search matches by meaning.
Example query:
“How to send email in ASP.NET MVC?”
Finds results like:
“C# SMTP mail example”“Send emails using System.Net.Mail”Even without matching words exactly.
2. Retrieval-Augmented Generation (RAG)
When you build an AI assistant or chatbot with your own data (PDFs, docs, SQL dumps), you:
Convert documents → embeddingsStore them in vector DBUser asks a questionFind most semantically relevant chunksSend them to LLM for grounded, accurate answers
Vector DB = the memory for your AI system.
3. Recommendation Systems
Find similar:
ProductsArticlesImagesMusicMovies
E.g., “users who liked this phone also liked…”
All done through vector similarity.
4. Image / Audio / Video Search
You can search images by description:
“Show me images with a red car on a road.”
Because both images and text can be turned into embeddings.
5. Anomaly Detection
Vectors can detect outliers:
Fraud detectionNetwork intrusionManufacturing defects
Outlier = vector that is far from cluster.
6. Deduplication and Clustering
Find similar documents or merge duplicates based on semantic similarity.
How Vector Search Works (simple example)
Convert text to vectorStore in vector DBConvert query to vectorCompute similarity (cosine / Euclidean)Return nearest neighbors
That’s it.
In Short
Concept
Explanation
Vector
Numeric representation of meaning
Vector DB
Stores embeddings and enables fast similarity search
Used For
RAG, semantic search, recommendations, image search, AI apps
and

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What is vector database? Why is it used?

Anubhav Kumar

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1 Answers

What is a Vector?

What is a Vector Database?

Why Is a Vector Database Used?

1. Semantic Search

2. Retrieval-Augmented Generation (RAG)

3. Recommendation Systems

4. Image / Audio / Video Search

5. Anomaly Detection

6. Deduplication and Clustering

How Vector Search Works (simple example)

In Short

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Concept	Explanation
Vector	Numeric representation of meaning
Vector DB	Stores embeddings and enables fast similarity search
Used For	RAG, semantic search, recommendations, image search, AI apps