#1 India's Top IT Training Institute

×

About Uncodemy

Know more about who we are and what we stand for.

About Us

About Us

Discover our mission to equip individuals with essential IT skills and industry expertise.

Read More →
UnCodeMy Gallery

UnCodeMy Gallery

Explore highlights from our IT training sessions and success stories.

Read More →
×

Free Resources

Learn, practice and plan your career — bilkul free.

Tutorials

Tutorials

Step-by-step written tutorials to learn any technology at your own pace.

Read More →
Free Counselling

Free Counselling

Book a free video counselling session and pick the right course for you.

Read More →
Online Compiler

Online Compiler

Write, run and test your code online — no setup required.

Read More →
🗄️ FREE · HNSW, IVF-PQ, FLAT

Vector Database Storage Calculator: Size Your Index

Work out how much memory and disk your embeddings, index and metadata will need.

  • 📐 Dimensions × precision
  • 🕸️ HNSW links
  • 📦 Metadata and replicas

How to use the Vector Database Storage Calculator

  1. 1. Enter your vectorsGive the number of vectors and the embedding dimensions.
  2. 2. Pick storage optionsChoose precision, index type and HNSW M or PQ code size, and add metadata and stored text per vector.
  3. 3. See the totalGet raw vector size, index overhead, metadata and the total with replicas.

How it's calculated

Raw vectors take vectors × dimensions × bytes per number: 4 bytes for float32, 2 for float16, 1 for int8 and 1/8 for binary. An HNSW index stores graph links: about 2 × M neighbour IDs of 4 bytes each per vector on the bottom layer, plus a little more for upper layers. IVF-PQ replaces full vectors with short codes (for example 64 bytes) plus an 8-byte ID. Metadata and any chunk text stored with each vector are added, and the total is multiplied by the number of replicas.

Worked example

The defaults are 10 lakh (1,000,000) vectors of 1,536 dimensions in float32 with an HNSW index (M = 16), 200 bytes of metadata and 2,000 bytes of chunk text each, and one copy. Raw vectors take 6.14 GB, metadata and text 2.2 GB and the HNSW links about 136.5 MB, for a total of 8.48 GB. Switch to int8 with a flat index and no stored text, and it drops to 1.54 GB of vectors plus 200 MB of metadata, 1.74 GB in all.

Planning tips

  • GB here means 10⁹ bytes. Add 20–50% headroom for logs, segments and deleted rows.
  • HNSW search is fastest when vectors and graph fit in RAM, so size RAM, not just disk.
  • Quantisation (int8, binary, PQ) saves a lot of memory but can lower recall; measure it on your queries.
  • Storing chunk text outside the vector database (for example in object storage) can cut its size sharply.

Frequently asked questions

Does every vector database store data this way?

No. Each product has its own layout and overhead, so treat this as a sizing estimate and confirm with your database's documentation or a test load.

How many vectors will I have?

Usually one per chunk. Our RAG chunk size calculator works this out from your documents.

Is the vector database storage calculator free?

Yes. You can open the vector database storage calculator and fill in everything without signing up. When you calculate storage for the first time, we ask once for your name and WhatsApp number; after that it, and every other Uncodemy tool, opens straight away.

More free tools

See all free tools