Pinecone, a vector database designed for scaling AI applications, has introduced a new bulk import feature aimed at simplifying the process of integrating substantial data volumes into its serverless infrastructure.

This recently unveiled capability, currently available in early access, is particularly beneficial for teams needing to import upwards of 100 million records, albeit with a maximum limit of 200 million records. The feature is also geared towards scenarios involving the onboarding of existing or new clients or the migration of production workloads from different providers to Pinecone.

The company asserts that this bulk import method allows for ingestion costs that are six times lower than those incurred through traditional upsert-based approaches. For example, the cost for importing 10 million records of 768 dimensions is approximately $30 using this bulk import option.

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Because the import process is asynchronous and operates in the background, customers are not required to optimize performance or monitor their import status; Pinecone handles these aspects automatically.

Data during the import process is sourced from a secure bucket in the customer’s object storage. This setup allows customers full control over their data access, including the option to terminate Pinecone’s access at any time.

In its early access phase, Pinecone restricts bulk imports to new serverless namespaces, which means data cannot be imported into existing namespaces. Currently, bulk import supports only Amazon S3 in serverless AWS regions, with plans to extend support to Google Cloud Storage and Azure Blob Storage in the forthcoming weeks.

Pinecone serverless has expanded its availability, adding to its existing AWS support to now include Google Cloud and Microsoft Azure platforms.

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