Vector Database Cost Calculator
Estimate the monthly cost of storing and querying your vectors across Pinecone, Weaviate, and Qdrant.
Once your documents are embedded, the resulting vectors have to live somewhere queryable — a vector database. Unlike embedding, which is a one-time cost, vector database costs are ongoing: providers typically charge for storage based on how many vectors you store and how many dimensions each one has, plus a separate rate for queries against the index. This calculator estimates your monthly bill across the major managed vector database providers from your vector count, embedding dimension, and expected query volume.
One vector per embedded document or chunk.
Set by your embedding model — commonly 384, 768, or 1536.
Cheapest Option
Qdrant Cloud
$5.03
per month
| Provider | Storage Cost | Query Cost | Total / Month |
|---|---|---|---|
| Qdrant Cloud | $5.00 | $0.03 | $5.03 |
| Weaviate Cloud | $6.50 | $0.03 | $6.54 |
| Pinecone Serverless | $8.00 | $0.04 | $8.04 |
Self-hosting with pgvector or a similar open-source option has no per-vector or per-query fee, but shifts the cost to your own database infrastructure — not modeled here since it depends entirely on your existing hosting setup.
How to Use This Calculator
1. Enter your vector count
One vector per embedded document or chunk in your index.
2. Enter your embedding dimension
Set by whichever embedding model produced your vectors — check its documentation if you're unsure.
3. Enter expected monthly queries
How many searches against the index you expect per month.
4. Compare the cheapest option
The table ranks every provider by total estimated monthly cost for your exact numbers.
How It Works
(vectors / 1M × storage_rate × dimension_multiplier) + (queries / 1M × query_rate)1M vectors at 768 dimensions with 100K monthly queries on a provider charging $8.00/1M vectors storage and $0.40/1M queries: (1 × $8.00 × 1.0) + (0.1 × $0.40) = $8.04/month.
Frequently Asked Questions
Is vector database cost a one-time or recurring expense?
Recurring. Unlike embedding (a one-time cost per document), storing vectors in a managed vector database is billed monthly for as long as the vectors remain stored and queryable.
Why does the number of dimensions affect cost?
Each dimension is a floating-point number in the vector. More dimensions means a physically larger vector to store, which is why storage cost scales with dimension count for the same number of vectors — a 1536-dimension index costs roughly double a 768-dimension index at the same vector count.
Is self-hosting always cheaper than a managed vector database?
Not necessarily. Self-hosting (for example with pgvector on your own Postgres instance) removes per-vector and per-query fees, but shifts the cost to your own infrastructure, plus the engineering time to operate and scale it. At small to moderate scale, a managed provider's usage-based pricing is often cheaper than running dedicated infrastructure.
Do all providers price storage and queries the same way?
No. The rates modeled here follow the common storage-plus-query shape most providers use, but exact pricing structures, minimum commitments, and included free tiers vary by provider — treat this as a comparative estimate, not a quote.
Common Mistakes
❌ Forgetting that dimension count directly drives storage cost
A 1536-dimension vector takes roughly twice the storage of a 768-dimension vector for the same document count. Switching to a higher-dimension embedding model to squeeze out marginally better retrieval quality can meaningfully increase your ongoing storage bill.
❌ Not accounting for re-indexing cost when switching embedding models
Every vector in your database has to be regenerated and re-stored if you switch embedding models, since vectors from different models aren't compatible — budget for a full storage-cost cycle, not just the marginal cost of new documents.
❌ Ignoring query cost when comparing providers
A provider with the cheapest storage rate isn't automatically the cheapest overall if your application is query-heavy rather than storage-heavy. Compare total monthly cost for your actual usage pattern, not storage rate alone.
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