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Google Cloud service
Vector Search
Topic in 1 exam domain
- Vector Search · Service
- Vector Search · Feature
- vector search · Concept
- vector search · Task
- vector search · Feature
Also called: Cloud SQL vector search, Matching Engine, MySQL vector search, semantic searches, similarity search, similarity searches, Vector queries, vector retrieval, Vector Search 1.0, Vector Search products, vector searches, vector similarity searches, Vertex AI Matching Engine
A service that supports deploying vector indexes to endpoints and provides features like autoscaling nodes based on workload demand.
Where this appears on the exam
1 objective in 1 of 5 domains
~15% of exam
Related topics
FoundationsBuilding blocksThis topicWorks alongsideembeddingsConceptVPC Service ControlsServiceIdentity and Access ManagementServiceApplication Default CredentialsFeatureMemorystore for ValkeyServicevector embeddingConceptBigQueryServiceCloud StorageServiceFirestoreServiceVertex AIServiceSpannerServiceCloud RunServiceDataflowService
Vector SearchFeature
Private Service ConnectFeatureGoogle Cloud StorageServiceVirtual Private CloudServiceCloud SQLServicePoints to what builds on itWorks with or alternative toHover or tap a line to see what connects the two
- Private Service Connect works with Vector Search From the official documentation: “Enabling Private Service Connect on a Vector Search endpoint is suited for use cases that:”
- Vector Search works with Vertex AI From the official documentation: “Reference architecture for a RAG-capable generative AI application using Vertex AI and Vector Search.”
- Cloud Storage works with Vector Search From the official documentation: “Cloud Storage: You can use the embeddings from a Cloud Storage bucket for building vector indexes and performing Vector Search.”
- Google Cloud Storage works with Vector Search From the official documentation: “Cloud Storage: You can use the embeddings from a Cloud Storage bucket for building vector indexes and performing Vector Search.”
- Spanner works with Vector Search From the official documentation: “Using the [Spanner to Agent Platform Vector Search workflow](https://github.com/cloudspannerecosystem/spanner-ai/tree/main/vertex-vector-search/workflows#readme), you can integrate your Spanner database with Vector Search to perform a vector similarity search on your Spanner…”
- Vector Search is part of BigQuery From the official documentation: “This document provides an overview of embeddings and vector search in BigQuery.”
- Vector Search depends on embeddings From the official documentation: “Vector search is built on embeddings.”
- Vector Search is part of Firestore From the official documentation: “The core workflow for vector search in Firestore consists of 4 steps.”
- Vector Search is part of Memorystore for Valkey From the official documentation: “Vector search on Memorystore for Valkey leverages multi-threaded queries, resulting in high query throughput (QPS) at low latency.”
- Vector Search is part of Spanner From the official documentation: “This document provides recommendations to optimize performance for vector search in Spanner.”
- Vector Search depends on vector embedding From the official documentation: “Vector search is built on embeddings.”
- Vector Search is part of Vertex AI From the official documentation: “Vertex AI features for AutoML Forecasting, AutoML Tabular, Batch Prediction, Online Prediction, Pipelines, Training, Vector Search, and Vizier are available in [10 additional Google Cloud regions](/vertex-ai/docs/general/locations#feature-availability).”
- Vector Search works with Virtual Private Cloud From the official documentation: “If you already have a VPC with private services access configured, you can use that VPC to peer with Vector Search.”
- Firestore depends on Application Default Credentials From the official documentation: “To authenticate to Firestore, set up Application Default Credentials.”
- Application Default Credentials works with Cloud Storage From the official documentation: “To authenticate to Cloud Storage, set up Application Default Credentials.”
- Vertex AI depends on Application Default Credentials From the official documentation: “To authenticate to Vertex AI, set up Application Default Credentials.”
- Application Default Credentials secures BigQuery From the official documentation: “To authenticate to BigQuery, set up Application Default Credentials.”
- BigQuery depends on Application Default Credentials From the official documentation: “To authenticate to BigQuery, set up Application Default Credentials.”
- Dataflow depends on Application Default Credentials From the official documentation: “To authenticate to Dataflow, set up Application Default Credentials.”
- Application Default Credentials works with Firestore From the official documentation: “To authenticate to Firestore, set up Application Default Credentials.”
- BigQuery is an alternative to Cloud Storage From the official documentation: “The `import_result_sink` must be a Cloud Storage path or a BigQuery table.”
- BigQuery works with Cloud Storage From the official documentation: “External BigQuery data source backed by Cloud Storage”
- Application Default Credentials works with BigQuery From the official documentation: “Create a BigQuery client using application default credentials.”
- Application Default Credentials secures Vertex AI From the official documentation: “To authenticate to Vertex AI, set up Application Default Credentials.”
- BigQuery works with Dataflow From the official documentation: “Read from BigQuery to Dataflow”
- BigQuery works with Cloud SQL From the official documentation: “Add credentials to connect BigQuery to Cloud SQL.”
- Cloud Run works with Cloud SQL From the official documentation: “Learn how to connect to Cloud SQL from Cloud Run”
- Application Default Credentials works with Dataflow From the official documentation: “To authenticate to Dataflow, set up Application Default Credentials.”
- VPC Service Controls secures BigQuery From the official documentation: “BigQuery data is protected with VPC Service Controls”
- Application Default Credentials secures Cloud Storage From the official documentation: “To authenticate to Cloud Storage, set up Application Default Credentials.”
- Application Default Credentials secures Spanner From the official documentation: “To authenticate to Spanner, set up Application Default Credentials.”
- Cloud Storage depends on Application Default Credentials From the official documentation: “To authenticate to Cloud Storage, set up Application Default Credentials.”
- Application Default Credentials works with Google Cloud Storage From the official documentation: “To authenticate to Cloud Storage, set up Application Default Credentials.”
- Application Default Credentials works with Spanner From the official documentation: “To authenticate to Spanner, set up Application Default Credentials.”
- Cloud SQL works with Cloud Storage From the official documentation: “When ingesting data from Cloud SQL, data is first staged to a Cloud Storage bucket.”
- Cloud SQL works with Private Service Connect From the official documentation: “You can use Private Service Connect to connect to a Cloud SQL instance from multiple VPC networks.”
- Cloud SQL works with Vertex AI From the official documentation: “This page describes how to integrate Cloud SQL with [Vertex AI](/vertex-ai/docs).”
- Spanner depends on Application Default Credentials From the official documentation: “To authenticate to Spanner, set up Application Default Credentials.”
- Cloud Run works with Cloud Storage From the official documentation: “Route Cloud Storage events to Cloud Run”
- BigQuery is an alternative to Google Cloud Storage From the official documentation: “The training data can be either a CSV file in Cloud Storage or a table in BigQuery.”
- BigQuery works with Google Cloud Storage From the official documentation: “Load Cloud Storage data into BigQuery”
- BigQuery works with Spanner From the official documentation: “Reverse ETL (BigQuery to Spanner)”
- Cloud SQL works with Identity and Access Management From the official documentation: “This page describes how Cloud SQL is integrated with IAM .”
- Cloud Storage works with Dataflow From the official documentation: “Write from Dataflow to Cloud Storage”
- Dataflow works with Spanner From the official documentation: “Use Dataflow to load data into Spanner.”
- Cloud Run depends on Application Default Credentials From the official documentation: “To authenticate to Cloud Run, set up Application Default Credentials.”
- Identity and Access Management secures Firestore From the official documentation: “This page describes the IAM permissions and roles for Firestore.”
- Application Default Credentials secures Dataflow From the official documentation: “To authenticate to Dataflow, set up Application Default Credentials.”
- Cloud Storage works with Identity and Access Management From the official documentation: “To learn how to use IAM with Cloud Storage, see [Using IAM Permissions](/storage/docs/access-control/using-iam-permissions).”
- VPC Service Controls secures Cloud Storage From the official documentation: “Storage Transfer Service supports transfers to Cloud Storage buckets protected by VPC Service Controls.”
- Application Default Credentials works with Cloud Run From the official documentation: “To authenticate to Cloud Run, set up Application Default Credentials.”
- Application Default Credentials works with Identity and Access Management From the official documentation: “To authenticate to IAM, set up Application Default Credentials.”
- Identity and Access Management secures BigQuery From the official documentation: “Access to BigQuery data from AlloyDB is managed through IAM.”
- Identity and Access Management secures Cloud Storage From the official documentation: “Cloud Storage uses Identity and Access Management (IAM) for authorization.”
- Application Default Credentials works with Vertex AI From the official documentation: “To authenticate to Vertex AI, set up Application Default Credentials.”
- BigQuery works with Identity and Access Management From the official documentation: “BigQuery uses Identity and Access Management (IAM) for authorization.”
- Cloud Run works with Firestore From the official documentation: “The Cloud Run app stores the result in Firestore.”
- Cloud Run works with Google Cloud Storage From the official documentation: “The Cloud Run function will receive syslog messages from FortiEDR via HTTP and write them to GCS.”
- Cloud Run works with Vertex AI From the official documentation: “The Cloud Run service can interact with Vertex AI services.”
- Cloud SQL works with Google Cloud Storage From the official documentation: “Imports data into a Cloud SQL instance from a SQL dump or CSV file in Cloud Storage.”
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