Overview: Connect app output to a data destination
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After you
create the
data ingestion stream and
add the
processing nodes to your app, you
must choose where to send the processed data. This data destination
("data sink") is the end point of your app
graph that accepts stream data without producing any stream data. The
destination you choose depends on how you use the app output data.
In the Google Cloud console, data destinations are available in the
Connectors section of the app graph page.
You can connect app output data to the following data destinations:
Vision Warehouse: Store original or analyzed video data that you
can view and query. Using a Vision Warehouse
allows you to specify annotations on whole or partial video clips.
BigQuery: Store data in BigQuery to use its offline
analytics capabilities. Using BigQuery
allows you to query streaming data, access and share analytical insights,
create reports and dashboards, and export BigQuery ML models for
online prediction.
Live stream data: If you want more granular control to act on real-time
analytics, you can receive the live output from your app.
For example, you can write code that uses live occupancy
count data to programmatically change staffing allocation.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Hard to understand","hardToUnderstand","thumb-down"],["Incorrect information or sample code","incorrectInformationOrSampleCode","thumb-down"],["Missing the information/samples I need","missingTheInformationSamplesINeed","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2025-08-28 UTC."],[],[],null,["# Overview: Connect app output to a data destination\n\nAfter you [create the\ndata ingestion stream](/vision-ai/docs/create-manage-streams) and [add the\nprocessing nodes](/vision-ai/docs/build-app#add-pretrained-model) to your app, you must choose where to send the processed data. This data destination (\"data sink\") is the end point of your app graph that accepts stream data without producing any stream data. The destination you choose depends on how you use the app output data.\n\n\u003cbr /\u003e\n\n*In the Google Cloud console, data destinations are available in the\n**Connectors** section of the app graph page.*\n\nYou can connect app output data to the following data destinations:\n\n1. **Vision Warehouse**: Store original or analyzed video data that you\n can view and query. Using a Vision Warehouse\n allows you to specify annotations on whole or partial video clips.\n\n For more information about sending app output data to a\n Vision Warehouse, see\n [Connect and store data to a warehouse](/vision-ai/docs/connect-warehouse).\n\n\n2. **BigQuery**: Store data in BigQuery to use its offline\n analytics capabilities. Using BigQuery\n allows you to query streaming data, access and share analytical insights,\n create reports and dashboards, and export BigQuery ML models for\n online prediction.\n\n For more information about sending app output data to BigQuery, see\n [Connect and store data to BigQuery](/vision-ai/docs/connect-bigquery).\n\n\n3. **Live stream data**: If you want more granular control to act on real-time\n analytics, you can receive the live output from your app.\n For example, you can write code that uses live occupancy\n count data to programmatically change staffing allocation.\n\n For more information about directly streaming app output data, see\n [Enable live stream output](/vision-ai/docs/enable-stream-output)."]]
