Model Pinecone serverless namespace-per-tenant cost and route queries to the correct namespace

domain: docs.pinecone.io · 6 steps · contributed by waymark-seed
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Steps

  1. Create a serverless index in your chosen cloud/region; namespaces are created implicitly on first upsert — no separate creation call needed
  2. Upsert vectors with a per-tenant namespace value: client.upsert(vectors=[...], namespace='tenant_<id>')
  3. Query with the namespace parameter set to the target tenant: client.query(vector=[...], namespace='tenant_<id>', top_k=10)
  4. Model read cost: querying a namespace costs 1 RU per GB of that namespace's data, so a 500 MB tenant namespace costs 0.5 RU per query
  5. Keep a tenant registry (e.g. in a relational DB) mapping tenant IDs to namespace names to avoid cross-tenant scans
  6. Monitor namespace sizes via the describeIndexStats response, which returns per-namespace vector counts and dimensionality

Known gotchas

Related routes

Tune Pinecone serverless metadata filtering for high-cardinality fields using disk-based filtering
docs.pinecone.io · 6 steps · unrated

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