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Database / pgvector basics Interview Questions

How do you install and enable pgvector in PostgreSQL?

pgvector installation has two steps: installing the extension binary on the server, and enabling it in each database where you want to use it. The extension name used in SQL is vector (not pgvector).

Installation methods
MethodCommand
Ubuntu/Debian (PostgreSQL APT repo)sudo apt install postgresql-17-pgvector
RHEL/CentOS (Yum repo)sudo yum install pgvector_17
macOS (Homebrew)brew install pgvector
DockerUse pgvector/pgvector Docker image
Condaconda install -c conda-forge pgvector
From sourcegit clone + make + make install
Managed (AWS RDS, Supabase, Neon, Azure)Enable via console or allowlist
-- Step 1: Enable in the database (run once per database)
CREATE EXTENSION vector;

-- Verify it is installed:
SELECT * FROM pg_extension WHERE extname = 'vector';

-- Upgrade an existing installation:
ALTER EXTENSION vector UPDATE;

-- On managed services (e.g. Azure), allowlist it first:
-- Then CREATE EXTENSION vector; in the database

-- Build from source (Linux):
-- git clone --branch v0.8.4 https://github.com/pgvector/pgvector.git
-- cd pgvector && make && sudo make install
-- Then in psql: CREATE EXTENSION vector;

Important naming note: although the project is universally called pgvector, the PostgreSQL extension name is vector. Always use CREATE EXTENSION vector (not pgvector). This distinction matters on managed services like Azure where you must allowlist the name vector.

What is the correct SQL command to enable pgvector in a PostgreSQL database?
What command verifies that the vector extension is installed in your PostgreSQL database?

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What is pgvector and what problem does it solve for developers? What are vector embeddings and why are they central to pgvector's use? How do you install and enable pgvector in PostgreSQL? What data types does pgvector provide and how do you define vector columns? What distance operators does pgvector provide and when do you use each? How do you insert and update vector data in pgvector? How do you perform a basic nearest-neighbour search with pgvector? What is the difference between exact and approximate nearest-neighbour search in pgvector? What is the HNSW index in pgvector and how do you create and tune it? What is the IVFFlat index in pgvector and how does it compare to HNSW? How do you use pgvector with Python and psycopg2? How do you use pgvector with SQLAlchemy and Python ORMs? How do you combine vector similarity search with SQL filters (hybrid search) in pgvector? How do you bulk-load vectors efficiently into pgvector? What operator classes must you use when creating pgvector indexes and why do they matter? How does pgvector fit into a RAG (Retrieval-Augmented Generation) pipeline? What is cosine distance vs cosine similarity and which does pgvector return? How do you check and monitor pgvector index creation progress? What is the pgvector maximum supported dimensions limit and how do you handle high-dimensional vectors? How do you use pgvector with LangChain for building AI applications? How does pgvector handle NULL values in vector columns? What are partial indexes in pgvector and when should you use them? How do you perform vector arithmetic and other vector functions in pgvector? How does pgvector compare to dedicated vector databases like Pinecone, Weaviate, and Qdrant? What is the difference between L1 and L2 distance in pgvector? How do you store and query vector embeddings with pgvector in a real schema design? What is halfvec and when should you use it to reduce storage costs? How do you handle vector dimensionality mismatches in pgvector? How do you use pgvector with Django? What are common performance tuning techniques for pgvector at scale? How do you implement semantic search with pgvector and a similarity threshold? How do you use pgvector with asyncpg or asyncio in Python? What is vector quantisation and how does pgvector support binary quantisation? How does pgvector integrate with managed PostgreSQL services? How do you use the inner product operator <#> with pgvector and when is it appropriate? How do you combine pgvector with full-text search (hybrid keyword + semantic search)? What PostgreSQL configuration parameters affect pgvector performance? How do you implement recommendation systems using pgvector? How do you use EXPLAIN and EXPLAIN ANALYZE to debug pgvector queries? What are best practices for a production pgvector deployment?
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