Architecture comparison

Target vs Walmart

Target runs closer to the foundational model (Native (own / self-hosted weights)) than Walmart (Off the LLM map (in-house non-LLM ML)). No shared foundational model — different bets.

Target

Retail

Proximity

Native (own / self-hosted weights)

Models

Google · Geminiproprietary / self-built models

Cloud · datastore

GCPown

Compliance

SOC 2PCI DSS

Architecture

Retailer on Google Cloud; store-companion + guest AI on Gemini over its own merchandising ML.

Walmart

Retail

Proximity

Off the LLM map (in-house non-LLM ML)

Models

—

Cloud · datastore

HybridApache KafkaSpark StreamingStormHDFSNoSQL databasesCassandra

Compliance

TLS/HTTPSenterprise network segmentationmulti-cloud container orchestration controlsconfiguration management/drift control

Architecture

Walmart’s production architecture is hybrid and multi-cloud: public-cloud workloads run across Azure and Google Cloud, while core infrastructure and brokers remain within Walmart-controlled private cloud environments.[1][2][7][10][15] The platform is heavily event-driven and containerized, with Kafka as a central backbone and WCNP/Kubernetes used for consumer workloads across clouds.[1][4]

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