Migrate from Pinecone to Qdrant

What You Need from Pinecone

API key — from the Pinecone console
Index name — the name of the index to migrate
Index host URL — the host endpoint shown in your index dashboard

Concept Mapping

Pinecone	Qdrant	Notes
Index	Collection	One-to-one mapping
Namespace	Payload field or separate collection	No direct equivalent — the tool migrates all namespaces. Use `--pinecone.namespace` to migrate a specific one
Metadata	Payload	Direct mapping
Sparse values	Sparse vectors	Mapped to `sparse_vector` named vector by default
`cosine`	`Cosine`	Direct mapping
`dotproduct`	`Dot`	Pinecone requires unit-normalized vectors for dotproduct
`euclidean`	`Euclid`	Direct mapping

Run the Migration

docker run --net=host --rm -it registry.cloud.qdrant.io/library/qdrant-migration pinecone \
    --pinecone.index-host 'https://your-index-host.pinecone.io' \
    --pinecone.index-name 'your-index' \
    --pinecone.api-key 'pcsk_...' \
    --qdrant.url 'https://your-instance.cloud.qdrant.io:6334' \
    --qdrant.api-key 'your-qdrant-api-key' \
    --qdrant.collection 'your-collection'

Migrating a Specific Namespace

docker run --net=host --rm -it registry.cloud.qdrant.io/library/qdrant-migration pinecone \
    --pinecone.index-host 'https://your-index-host.pinecone.io' \
    --pinecone.index-name 'your-index' \
    --pinecone.api-key 'pcsk_...' \
    --pinecone.namespace 'my-namespace' \
    --qdrant.url 'https://your-instance.cloud.qdrant.io:6334' \
    --qdrant.api-key 'your-qdrant-api-key' \
    --qdrant.collection 'your-collection'

All Pinecone-Specific Flags

Flag	Required	Description
`--pinecone.index-name`	Yes	Name of the Pinecone index
`--pinecone.index-host`	Yes	Host URL of the Pinecone index
`--pinecone.api-key`	Yes	Pinecone API key
`--pinecone.namespace`	No	Specific namespace to migrate
`--pinecone.service-host`	No	Custom Pinecone service host

Qdrant-Side Options

Flag	Default	Description
`--qdrant.id-field`	`__id__`	Payload field name for original Pinecone IDs
`--qdrant.sparse-vector`	`sparse_vector`	Named vector for Pinecone sparse values

Gotchas

Score scaling: Pinecone cosine similarity returns values in [0, 1] (rescaled). Qdrant returns [-1, 1]. Rankings are identical, but raw scores won’t match.
Metadata size limits: Pinecone limits metadata to 40KB per vector. Qdrant has no per-payload size limit, so data is preserved as-is.
Namespace strategy: If you have multiple namespaces, decide upfront whether to merge them into a single Qdrant collection (using a namespace payload field for filtering) or create separate collections.

Next Steps

After migration, verify your data arrived correctly with the Migration Verification Guide.

Was this page useful?

On this page: