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A private endpoint can keep traffic to a managed vector database off the public internet, but it does not move that database into your data center or make the provider’s service customer-operated. To keep AI data inside a particular boundary, map the whole path: source documents, embeddings, index, prompts, retrieval results, model calls, logs, backups, and administrative access. Then choose between private access to a managed service and genuinely local or disconnected operation.

What does “inside the boundary” mean for a vector store?

A vector store holds embeddings—numeric representations of content—so an AI system can retrieve relevant material by similarity. But the index is only one part of the system. Documents must be processed into embeddings; applications send queries; retrieval may return passages to a language model; and services produce logs, backups, and operational records.

“Disconnected vector store” is a useful description for separating vector storage and related AI work from an application or source-data environment, not a formal deployment standard. Before choosing a design, define the boundary you need: an organization-owned data center, a customer-controlled virtual network, a cloud region, or a regulatory or security perimeter. Those boundaries are not interchangeable.

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Trace every copy and operation

For each component, record where it runs, who operates it, and whether data crosses the boundary. Include:

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A private network path answers how traffic reaches a service. It does not, by itself, answer where the service, its copies, or its operators are located.

Does a private endpoint mean the service is on-premises?

No. A private endpoint can provide private connectivity to a provider-managed cloud service. That can reduce exposure to the public internet, but the service still runs in the provider’s environment unless the deployment is specifically local. AWS documentation describes PrivateLink access to S3 Vectors from a VPC and on-premises connectivity through Direct Connect or VPN; it describes a private route to a managed service, not an on-premises S3 Vectors installation. Google Cloud documents Private Service Connect and internal VPC IP addresses for consuming managed Vector Search endpoints. These are private-access patterns, not air-gapped deployments.

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A private path may help address a requirement for private network connectivity. It is not, on its own, proof that a full regulatory or security obligation is met. Confirm the service location, region, data handling, contract, configuration, and support arrangements against the actual requirement.

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Which deployment patterns are available?

Pattern What it means Example documented by the provider Main trade-off
Managed service with a private endpoint Traffic uses a private connection, while the provider operates the cloud service. AWS documents VPC interface endpoints through PrivateLink for S3 Vectors, and on-premises access through Direct Connect or VPN. Private connectivity does not make the service local or customer-operated.
Managed service through a private service connection A customer network privately consumes a provider-managed endpoint. Google Cloud documents Private Service Connect and internal VPC IP addresses for Vector Search endpoints. The service remains managed; this is not a disconnected or air-gapped arrangement.
Data-center or air-gapped AI services AI services run locally without dependence on public-cloud or internet connectivity. Oracle describes its Private AI Services Container as designed for data-center deployment without public-cloud or internet dependency, with local embedding and LLM services and the ability to offload vector-index work. The operator takes on more responsibility for infrastructure and lifecycle operations. Oracle’s description applies to its product, not every local deployment.
Postgres-centered vector and relational data Vectors and relational data can be handled within a database architecture. EDB’s vendor-authored white paper describes EDB PG AI with pgvector across on-premises, cloud, and hybrid configurations. Check current product details and deployment controls; the cited description is vendor material.
Retrieval platform with private deployment A retrieval platform provides controls at query time and may offer private deployment options. Vectara documentation describes tenant isolation, retrieval-time role filtering, and VPC, on-premises, and air-gapped deployment options. Validate which controls and deployment characteristics apply to the specific configuration and contract.

These examples describe different control boundaries, not a performance or security ranking. Provider documentation and a vendor white paper describe their own products; they are not independent audits of a particular deployment.

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How should you choose between managed and local storage?

Decide based on the data path and the control you require, rather than the word “private” in a service description.

Choose private access to a managed service when

  • Your requirement is to keep network traffic on a private path, while a provider-operated service in an approved cloud environment is acceptable.
  • You have verified the relevant region, data flows, identity controls, support access, retention, and contractual terms.
  • Your team prefers the provider to operate the service, and the remaining data-location and governance conditions are acceptable.

Consider local or air-gapped operation when

  • Your defined boundary excludes a provider-managed cloud service or internet-dependent operation.
  • Embedding, inference, indexing, and retrieval must run within the organization’s data center or disconnected environment.
  • Your organization can take responsibility for infrastructure, capacity, updates, recovery, and operational security.

Consider a database-centered design when

  • You want to evaluate whether vector and relational data can share an existing database architecture.
  • Keeping application data and retrieval controls closer together simplifies your governance model.
  • You have checked the database’s current vector capabilities, deployment options, authorization model, and operational requirements rather than relying only on a product overview.

What controls matter at retrieval time?

Protecting the index at rest is not enough if retrieval can expose passages a user is not authorized to see. The application needs to enforce access rules when it selects and returns results, and those rules should match the identity and permissions used for the underlying content.

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  • Tenant separation: establish how one customer or business unit is prevented from retrieving another’s data.
  • Retrieval-time authorization: test whether document-level or role-based permissions are applied when results are fetched, not just when data is ingested.
  • Identity and keys: determine which identity provider and key-management arrangements apply, and who can administer them.
  • Audit and lifecycle: check what is recorded, how long data and logs persist, and how deletion propagates to indexes, replicas, and backups.
  • Operations and support: identify who can access the system for maintenance, troubleshooting, or incident response.

Vectara documentation describes tenant isolation and retrieval-time role filtering. EDB’s white paper describes database controls for its platform. These are vendor descriptions; they do not establish that a particular deployment is configured correctly. Verify the actual implementation and test access boundaries with representative identities and data.

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What operating work shifts when storage moves inside?

A managed service with private connectivity keeps the service operation with the provider while giving the customer a private network path. Local and air-gapped deployments shift more of the stack to the organization. That can include hardware and capacity planning, availability, patching, model and index updates, backup and recovery, monitoring, and incident response.

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Do not treat this as a simple cost comparison: the available product descriptions do not establish a like-for-like cost or performance result. Instead, assign an owner for each responsibility and confirm that the team can meet the required availability and recovery targets without relying on unavailable cloud services or internet access.

How to evaluate vendor figures and claims

Provider-specific figures can help explain a service’s stated design or conditions, but they do not rank different architectures.

  • AWS states that S3 storage underpinning S3 Vectors is designed for 99.999999999% (11 nines) durability. The year is not stated on the cited security page. This is an AWS-published design statement, not an independently measured comparison.
  • Google Cloud says a deployed Vector Search index with fewer than two replicas per shard is excluded from the service-level agreement described on its documentation page. This is a condition for that stated SLA, not a general recommendation for every vector system.
  • Oracle’s product page, dated March 24, 2026, says six popular vector embedding models ship with its container and that customers may download additional models. This is a product-specific model count.

Oracle’s product page also says, “Your AI data never leaves your realm.” Treat that as Oracle’s product-page wording, not as an independently audited or universal guarantee. The practical meaning depends on the deployment, configuration, contract, and support arrangements.

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A practical boundary review before deployment

  1. Draw the data flow. Follow a document from ingestion through embedding, indexing, query, retrieval, model inference, logging, backup, and deletion.
  2. Label the boundary. Mark which components are in an organization-owned data center, customer-controlled network, provider cloud, or another security perimeter.
  3. Check every network connection. Distinguish public endpoints, private endpoints, hybrid links, and offline operation. Record where each connection terminates.
  4. Test authorization and isolation. Use accounts with different roles and tenants to verify that retrieval returns only permitted content.
  5. Assign operating ownership. Confirm who patches, monitors, scales, restores, and responds to incidents for each component.
  6. Confirm terms and configuration. Review region, retention, deletion, key custody, administrative access, and support provisions for the chosen deployment.

Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.