What inputs does the Embeddings DB Cost need?

It takes 5 inputs: vectorCount, dim, queriesPerDay, ingestPerDay, retentionDays. Outputs returned: vendors, cheapestVendor, storageGb.

Can I verify the Embeddings DB Cost with a worked example?

Yes. With 1M vectors, dim 1536, 50k queries/day, 5k ingest/day, 365 day retention. the tool returns storageGb ≈ 7.15. Cheapest vendor varies by inputs — see the live tool.

Where does the Embeddings DB Cost get its benchmark data?

Reference data is sourced from: Pinecone pricing (as of 2026-04); Cloudflare R2 pricing (as of 2026-04); DigitalOcean Managed Databases pricing (as of 2026-04); Turbopuffer pricing (as of 2026-04).

What can the Embeddings DB Cost not tell me?

Known limitations: Vendor pricing changes; re-check if the as-of date has aged 60+ days. Workload-fit factors (latency, recall, namespacing) are not modeled — pure cost only.

Methodology: Embeddings DB Cost

1. Scope

Computes monthly cost across four vector DB options (Pinecone Standard, Postgres+pgvector managed, LanceDB on R2, Turbopuffer) using vendor public pricing snapshots as of 2026-04.

2. Inputs and outputs

Inputs

vectorCount number
dim number
queriesPerDay number
ingestPerDay number
retentionDays number

Outputs

vendors

Per-vendor monthly cost in USD with brief sourcing notes.
cheapestVendor

Vendor name with the lowest monthlyCost.
storageGb

vectors × dim × 4 bytes × 1.25 / 1 GB.

Engine source: src/lib/embeddings-db-cost/engine.ts

3. Formula / scoring logic

storage_bytes = vectors × dim × 4 × 1.25
queries_mo = queries_day × 30
ingest_mo = ingest_day × 30
then per-vendor list pricing applied

4. Assumptions

Float32 storage. Quantized indices (int8, binary) cut storage 2–32× and aren't modeled.
Replication / backup costs excluded.
LanceDB self-hosted compute (CPU/RAM) excluded — only object-storage and op costs are in.

5. Data sources

Pinecone pricing as of 2026-04
Cloudflare R2 pricing as of 2026-04
DigitalOcean Managed Databases pricing as of 2026-04
Turbopuffer pricing as of 2026-04

6. Known limitations

Vendor pricing changes; re-check if the as-of date has aged 60+ days.
Workload-fit factors (latency, recall, namespacing) are not modeled — pure cost only.

7. Reproducibility

Input
1M vectors, dim 1536, 50k queries/day, 5k ingest/day, 365 day retention.

Expected output
storageGb ≈ 7.15. Cheapest vendor varies by inputs — see the live tool.

8. Change log

2026-05-08 methodology first published. Pricing snapshot 2026-04.

Worked example

Run live against the same engine this site ships (/engines/embeddings-db-cost.js). The inputs and outputs below are recomputed on every build and independently re-verified in CI — they are never hand-authored.

Input

tool: embeddings_db_cost
vector_count: 1000000
dim: 1536
queries_per_day: 50000
ingest_per_day: 5000
retention_days: 365

Output

vendors[0].vendor: Pinecone
vendors[0].monthlyCost: 3.46
vendors[0].notes: Pinecone Standard list pricing 2026-04: $0.33/M reads, $4/M writes, $0.33/GB-mo storage.
vendors[1].vendor: Postgres+pgvector
vendors[1].monthlyCost: 35
vendors[1].notes: DigitalOcean managed Postgres baseline ($35/mo, includes 25GB; $0.20/GB-mo overage). Self-hosted equivalent.
vendors[2].vendor: LanceDB
vendors[2].monthlyCost: 7.53
vendors[2].notes: LanceDB on Cloudflare R2 list pricing 2026-04: $0.015/GB-mo, $4.50/M ops. Self-hosted compute not included.
vendors[3].vendor: Turbopuffer
vendors[3].monthlyCost: 1.08
vendors[3].notes: Turbopuffer list pricing 2026-04: $0.10/GB-mo, $0.04/M reads, $2/M writes.
cheapestVendor: Turbopuffer
cheapestMonthlyCost: 1.08
storageGb: 7.15

Frequently asked questions

What does the Embeddings DB Cost calculate?: Computes monthly cost across four vector DB options (Pinecone Standard, Postgres+pgvector managed, LanceDB on R2, Turbopuffer) using vendor public pricing snapshots as of 2026-04.
What inputs does the Embeddings DB Cost need?: It takes 5 inputs: vectorCount, dim, queriesPerDay, ingestPerDay, retentionDays. Outputs returned: vendors, cheapestVendor, storageGb.
What formula does the Embeddings DB Cost use?: The exact computation is: storage_bytes = vectors × dim × 4 × 1.25; queries_mo = queries_day × 30; ingest_mo = ingest_day × 30; then per-vendor list pricing applied
Can I verify the Embeddings DB Cost with a worked example?: Yes. With 1M vectors, dim 1536, 50k queries/day, 5k ingest/day, 365 day retention. the tool returns storageGb ≈ 7.15. Cheapest vendor varies by inputs — see the live tool.
Where does the Embeddings DB Cost get its benchmark data?: Reference data is sourced from: Pinecone pricing (as of 2026-04); Cloudflare R2 pricing (as of 2026-04); DigitalOcean Managed Databases pricing (as of 2026-04); Turbopuffer pricing (as of 2026-04).
What can the Embeddings DB Cost not tell me?: Known limitations: Vendor pricing changes; re-check if the as-of date has aged 60+ days. Workload-fit factors (latency, recall, namespacing) are not modeled — pure cost only.