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AI/ML BYOC: Pinecone vector database managed service expands to AWS, Azure & GCP Vector database-as-a-Service supplier Pinecone has released its proprietary cloud lock by adding support for the AWS, Azure and Google clouds, and is aiming to head fully into the on-prem world. A vector database stores the mathematically transformed tokens generated by a user’s natural language input to a large language model (LLM). Pinecone provides a managed vector database service to store, access and use these vectors. Its bring-your-own-cloud (BYOC) strategy has a customer’s vector data - the data plane - living in their public cloud area but still managed through the Pinecone control plane for operations such as resource lifecycle, authentication, and service health. This control plane does not store or process customer content or request payloads. The public cloud data plane stores, processes, and serves customer data and knowledge. AI agents and applications connect directly to this for read and write operations. The only data shared with Pinecone are anonymized operational metrics and traces for monitoring and support. With BYOC, the data plane runs inside the customer's selected cloud account and region, including those beyond where Pinecone's standard service is available. Vectors, documents, metadata, and request payloads remain within the customer-controlled boundary. Customers retain access to Pinecone’s support and engineering teams for troubleshooting, incident response, and ongoing operational guidance. Pinecone does not require SSH, VPN, inbound network access, or a standing cross-account IAM role to manage the service. Upgrades, scaling actions, and maintenance work are retrieved using an outbound call from the Pinecone control plane and executed locally. This allows Pinecone to manage the database without a persistent access path into the customer environment. BYOC works alongside SSO, RBAC, SCIM + SAML, audit logging, encryption, and private-networking controls available with Pinecone's Enterprise plan so customers can have complete confidence in ensuring their proprietary knowledge is secure. Customer admin teams use the same Pinecone APIs, SDKs, and control plane workflows across the BYOC and standard deployments. This means each workload can use the deployment model that fits its data governance and access requirements without creating a separate development path. Toyota Motor North America (TMNA) was one of Pinecone’s first BYOC customers to deploy it in production. TMNA used Pinecone to this way with its decades of proprietary manufacturing knowledge kept secure inside Toyota’s environment and not exposed to Pinecone’s own managed service. Kordel France, Head of AI Engineering at Toyota Motor North America, said: ”Decades of manufacturing know-how live in our documentation, and that institutional knowledge is one of the most valuable assets we have. It also happens to be complex — highly structured engineering data sitting alongside unstructured process documents, across a lot of formats and a lot of different access patterns. Pinecone BYOC runs inside our own environment, so that knowledge never leaves our boundary and is served only to models we’ve already vetted.” Pinecone wants to go further, and work in a customer’s on-premises environment. Its developing a fully self-managed option for air-gapped and highly restricted networks where both the control plane and data plane will run inside the customer environment. Read more about all this in a Pinecone BYOC product page here and from BYPC documentation here. Bootnote Pinecone is following its competitors' examples. Zilliz Cloud documents regions on all three providers and offers both SaaS and BYOC (Bring Your Own Cloud) on AWS, Google Cloud, and Microsoft Azure. Feature availability can vary by region and plan (for example on-demand compute is not equally available everywhere). Weaviate can be self-hosted, with deployment on Kubernetes on AWS (EKS), Azure (AKS), or GCP (GKE). The managed Weaviate Shared Cloud is available on GCP and AWS (AWS Shared Cloud went GA in US East and Europe Frankfurt). Dedicated/enterprise deployments are described as covering AWS, GCP, and Azure. There is also an Azure Marketplace listing for running Weaviate in a customer Azure tenant. Qdrant supports AWS, Azure, and GCP or your own Hybrid Cloud infrastructure.
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