--- title: "Connect Google BigQuery to Azure Cosmos Db - APIANT.ai" description: "When \"New Job Completed\" fires in Google BigQuery, your agent runs \"Create Document\" in Azure Cosmos Db." canonical: "https://apiant.ai/connect/google-bigquery-to-azure-cosmos-db" --- # Connect Google BigQuery to Azure Cosmos Db When **New Job Completed** fires in [Google BigQuery](https://apiant.ai/connections/google-bigquery), your agent runs **Create Document** in [Azure Cosmos Db](https://apiant.ai/connections/azure-cosmos-db). Describe the whole flow and it is built, tested on every scenario and kept running. Google BigQuery **4** triggers Google BigQuery **10** actions Azure Cosmos Db **14** actions What the catalog holds today. Ask for anything missing and your agent reads the API documentation and adds it. ## What do you want Google BigQuery and Azure Cosmos Db to do together? Give your AI client this address. `https://mcp.apiant.ai` One connection does both: ask your client to act in an app once, or have it build an automation that keeps running. Any client that takes a remote MCP server. Nothing to install. Create your free account, then sign in once in your browser. ### Set it up in your client ### Claude Code Run this in the directory you want to work in. `claude mcp add --transport http -s project apiant-ai https://mcp.apiant.ai` Start Claude Code there, approve the server, and sign in in the browser page it opens. [Claude Code guide (opens in a new tab)](https://apiant.ai/docs/mcp/claude-code) ### Claude, web and desktop Open Customize, then Connectors, then Add custom connector, and paste the address. On Team and Enterprise an owner adds it first. [Setup guide (opens in a new tab)](https://apiant.ai/docs/mcp) ### Cursor Add the address to your MCP configuration as a server URL. Cursor signs you in in your browser. [Setup guide (opens in a new tab)](https://apiant.ai/docs/mcp) ### Zed Open Settings, then AI, then MCP Servers, then Add Server, then Add Remote Server. [Setup guide (opens in a new tab)](https://apiant.ai/docs/mcp) ### Codex and the ChatGPT desktop app Open Settings, then MCP servers, then Add server, and choose Streamable HTTP. From the terminal, Codex takes the address with its own add command and then signs you in. [Setup guide (opens in a new tab)](https://apiant.ai/docs/mcp) ### Any other MCP client Paste the address where the client asks for a remote MCP server URL, and name the server apiant-ai where it lets you. APIANT's skills reach the client over the same connection. [Setup guide (opens in a new tab)](https://apiant.ai/docs/mcp) Example flows ## What Google BigQuery can start in Azure Cosmos Db - When **New Job Completed** in Google BigQuery then **Create Document** in Azure Cosmos Db - When **New Row** in Google BigQuery then **Query Documents** in Azure Cosmos Db Starting points drawn from the triggers and actions in the catalog today. Describe the flow you need, at any depth, and your agent builds it and tests every scenario before it ships. Everything your agent can do with Google BigQuery and Azure Cosmos Db ## Triggers and actions 4 triggers · 24 actions - Trigger **New Job Completed** Triggers when a BigQuery job in the project finishes, whether it succeeded or failed. - Trigger **New Row** Triggers when a new row is added to a table. New rows are detected by a column you name that increases for newer rows, such as a creation time or a sequential ID. - Trigger **Query Job Completed (With Row Data)** Triggers when a SELECT query job in the project finishes successfully, and includes its result rows. - Trigger **Updated Row** Triggers when a row in a table is added or changed, detected by a last-updated timestamp column you name. - Action **Create Row** Creates a new row of data in a table. Note: Does not create a job. - Action **Create Rows** Creates new rows of data in a table (accepts line items). Note: Does not create a job. - Action **Delete Rows** Deletes every row in a table whose match column equals the value you give. - Action **Find One Row** Finds the first row in a table whose column equals the value you give. - Action **Get Rows for Job Completed** Returns the result rows of a finished query job. - Action **Import Data** Imports a JSON, CSV, Avro or Parquet file from Cloud Storage into a table. Waits up to about 40 seconds for the import to finish; larger imports keep running in BigQuery and return state RUNNING. - Action **List Datasets** Returns the datasets in a Google Cloud project. - Action **List Tables** Returns the tables in a BigQuery dataset. - Action **Run a Query** Runs a SQL query against a table in BigQuery. - Action **Update Row(s)** Updates every row in a table whose match column equals the value you give, setting the columns you choose. - Action **Create Container** Creates a new container in a Cosmos DB database, partitioned on the property you choose. - Action **Create Database** Creates a new database in the Azure Cosmos DB account, optionally with shared provisioned throughput. - Action **Create Document** Creates a new document in a Cosmos DB container, or replaces an existing one with the same id when upsert is on. - Action **Delete Container** Deletes a container, and every document in it, from a Cosmos DB database. - Action **Delete Database** Deletes a database, and every container and document in it, from the Azure Cosmos DB account. - Action **Delete Document** Deletes one document from a Cosmos DB container. - Action **Get Container** Returns one container in a Cosmos DB database, including its partition key and indexing policy. - Action **Get Database** Returns one database in the Azure Cosmos DB account by its name. - Action **Get Document** Returns one document from a Cosmos DB container by its id and partition key. - Action **List Containers** Returns every container in a Cosmos DB database. - Action **List Databases** Returns every database in the Azure Cosmos DB account. - Action **List Documents** Returns the documents in a Cosmos DB container. - Action **Query Documents** Runs a Cosmos DB SQL query against a container and returns the matching documents. - Action **Replace Document** Replaces the whole body of an existing document in a Cosmos DB container. ## Each app on its own - [ **Google BigQuery** BigQuery is Google's serverless and highly scalable enterprise data warehouse, designed to make all your...](https://apiant.ai/connections/google-bigquery) - [ **Azure Cosmos Db** Fully managed NoSQL and vector database for storing and querying JSON documents at global scale.](https://apiant.ai/connections/azure-cosmos-db) Reviews ## What our customers say ## More from Google BigQuery - [ **Google BigQuery to HTML to Image** HTML to Image is a Powerful Image Generation API to convert HTML/CSS to Image and to take screenshots of...](https://apiant.ai/connect/google-bigquery-to-html-to-image) - [ **Google BigQuery to PaperClean** Clean document photos for printing, remove shadows, fix lighting](https://apiant.ai/connect/google-bigquery-to-paperclean) - [ **Google BigQuery to Resend** Resend is the email API for developers. It's designed for you to build, test, and send transactional and...](https://apiant.ai/connect/google-bigquery-to-resend) - [ **Google BigQuery to TypeSafe** TypeSafe's Jev model answers typed questions about a piece of content and tells you how certain it is.](https://apiant.ai/connect/google-bigquery-to-typesafe) - [ **Google BigQuery to HubSpot** HubSpot is your all-in-one stop for all of your marketing software needs.](https://apiant.ai/connect/google-bigquery-to-hubspot) - [ **Google BigQuery to Salesforce** Salesforce is a leading enterprise customer relationship management (CRM) platform.](https://apiant.ai/connect/google-bigquery-to-salesforce) ## More into Azure Cosmos Db - [ **HubSpot to Azure Cosmos Db** HubSpot is your all-in-one stop for all of your marketing software needs.](https://apiant.ai/connect/hubspot-to-azure-cosmos-db) - [ **Salesforce to Azure Cosmos Db** Salesforce is a leading enterprise customer relationship management (CRM) platform.](https://apiant.ai/connect/salesforce-to-azure-cosmos-db) - [ **Slack to Azure Cosmos Db** Slack is a messaging platform for teams. Post messages, manage channels, users, reminders, and react to...](https://apiant.ai/connect/slack-to-azure-cosmos-db) - [ **Google Sheets to Azure Cosmos Db** Google Sheets is Google's online spreadsheet app for creating, editing and sharing spreadsheets.](https://apiant.ai/connect/google-sheets-to-azure-cosmos-db) - [ **Gmail to Azure Cosmos Db** Gmail is Google’s email service, featuring spam protection, search functions, and seamless integration with...](https://apiant.ai/connect/gmail-to-azure-cosmos-db) - [ **Google Calendar to Azure Cosmos Db** Google Calendar is a time management tool providing scheduling features, event reminders, and integration...](https://apiant.ai/connect/google-calendar-to-azure-cosmos-db) Questions ## Google BigQuery and Azure Cosmos Db, answered ### ### What can start an automation from Google BigQuery? Any of Google BigQuery's 4 triggers in the catalog, including New Job Completed, New Row, Query Job Completed (With Row Data) and Updated Row. Describe the moment in plain language and your agent picks the right one. ### ### What can your agent do in Azure Cosmos Db when something happens in Google BigQuery? Any of Azure Cosmos Db's 14 actions, including Create Container, Create Database, Create Document and Get Container. Your agent maps the data both ways and tests every scenario before it ships. ### ### Can it also run from Azure Cosmos Db to Google BigQuery? Azure Cosmos Db has no triggers in the catalog today, so automations start in Google BigQuery. If you need the other direction, ask: your agent reads Azure Cosmos Db's API documentation and adds it. ### ### Do I have to build a connector for Google BigQuery or Azure Cosmos Db? No. Both are in the catalog with their triggers and actions. You describe the automation; your agent builds it, tests every scenario and keeps it running. ### ### Can my AI client use Google BigQuery and Azure Cosmos Db without building an automation? Yes. With your AI client connected to APIANT, ask it to do something in either app once and it runs that action on the spot. Ask for an automation and your agent builds it, tests every scenario and keeps it running. One connection covers both. ### ### What happens when something fails? Your agent works that out for you. It plans the failure paths along with the happy path, then tests every scenario before it ships. ### ### Is there a free plan? Yes. Every plan includes the agent, including free, and building from your own AI client spends no assistant credits.