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integrationMicrosoft SQL node

HTTP Request and Microsoft SQL integration

Save yourself the work of writing custom integrations for HTTP Request and Microsoft SQL and use n8n instead. Build adaptable and scalable Development, Core Nodes, and Data & Storage workflows that work with your technology stack. All within a building experience you will love.

How to connect HTTP Request and Microsoft SQL

  • Step 1: Create a new workflow
  • Step 2: Add and configure nodes
  • Step 3: Connect
  • Step 4: Customize and extend your integration
  • Step 5: Test and activate your workflow

Step 1: Create a new workflow and add the first step

In n8n, click the "Add workflow" button in the Workflows tab to create a new workflow. Add the starting point – a trigger on when your workflow should run: an app event, a schedule, a webhook call, another workflow, an AI chat, or a manual trigger. Sometimes, the HTTP Request node might already serve as your starting point.

HTTP Request and Microsoft SQL integration: Create a new workflow and add the first step

Step 2: Add and configure HTTP Request and Microsoft SQL nodes

You can find HTTP Request and Microsoft SQL in the nodes panel. Drag them onto your workflow canvas, selecting their actions. Click each node, choose a credential, and authenticate to grant n8n access. Configure HTTP Request and Microsoft SQL nodes one by one: input data on the left, parameters in the middle, and output data on the right.

HTTP Request and Microsoft SQL integration: Add and configure HTTP Request and Microsoft SQL nodes

Step 3: Connect HTTP Request and Microsoft SQL

A connection establishes a link between HTTP Request and Microsoft SQL (or vice versa) to route data through the workflow. Data flows from the output of one node to the input of another. You can have single or multiple connections for each node.

HTTP Request and Microsoft SQL integration: Connect HTTP Request and Microsoft SQL

Step 4: Customize and extend your HTTP Request and Microsoft SQL integration

Use n8n's core nodes such as If, Split Out, Merge, and others to transform and manipulate data. Write custom JavaScript or Python in the Code node and run it as a step in your workflow. Connect HTTP Request and Microsoft SQL with any of n8n’s 1000+ integrations, and incorporate advanced AI logic into your workflows.

HTTP Request and Microsoft SQL integration: Customize and extend your HTTP Request and Microsoft SQL integration

Step 5: Test and activate your HTTP Request and Microsoft SQL workflow

Save and run the workflow to see if everything works as expected. Based on your configuration, data should flow from HTTP Request to Microsoft SQL or vice versa. Easily debug your workflow: you can check past executions to isolate and fix the mistake. Once you've tested everything, make sure to save your workflow and activate it.

HTTP Request and Microsoft SQL integration: Test and activate your HTTP Request and Microsoft SQL workflow

Flexible currency rate uploads for SAP B1 with AI validation & multiple sources

This workflow automates currency rate uploads into SAP Business One via Service Layer, using flexible input sources such as JSON (API), SQL Server, Google Sheets, or manual values. It leverages logic branching, AI validation, and logging for complete control and traceability.

++⚙️ HOW IT WORKS:++
🔹 1. Receive Data via Webhook

The workflow listens on the endpoint /formulario-datos via HTTP POST.

The request body should include:

origen: one of JSON, SQL, GoogleSheets, or Manual

Depending on the value, the flow branches accordingly.

🔹 2. Authenticate with SAP Business One

A POST request is sent to SAP B1’s Login endpoint.

A session cookie (B1SESSION) is retrieved and used in all subsequent API calls.

🔹 3. Switch by Origin
The flow branches into four processing paths based on origen:

JSON:

The payload is normalized using OpenAI to extract an array of rates.

Each rate is sent to SAP individually after parsing.

SQL:

The SQL query provided in the payload is executed on a connected Microsoft SQL Server.

The results are checked by AI to validate the date format.

If valid, rates are sent to SAP.

GoogleSheets:

Rates are pulled from a connected spreadsheet.

Each entry is sent to SAP in sequence.

Manual:

Uses currency, rate, and rateDate directly from the webhook payload.

Sends the result directly to SAP.

🔹 4. AI-Powered Enhancements (Optional but enabled)

Normalize JSON:
Uses OpenAI (LangChain node) to convert any messy structure into a uniform array under the key rate.

Date Formatting:
Another OpenAI call ensures RateDate is in yyyyMMdd format (required by SAP), converting from ISO, timestamp, or other formats.

🔹 5. Send to SAP Business One (Service Layer)
All paths send a POST request to:

/SBOBobService_SetCurrencyRate
With a payload such as:

{
"Currency": "USD",
"Rate": "0.92",
"RateDate": "20250612"
}

🔹 6. Log Results

All success/failure results are appended to a Google Sheets log (LOGS_N8N)

The log includes method, URL, sent payload, status code, and message.

++🛠 SETUP STEPS:++

1️⃣ Create Required Credentials:
Go to Credentials > + New Credential and configure:

SAP Business One (Service Layer)

Type: HTTP Request Auth or Token

Base URL: https://<your-host>:50000/b1s/v1/

Provide Username, Password, and CompanyDB via variables or fields

Google Sheets

OAuth2 connection to a Google account with access

Microsoft SQL Server

SQL login credentials and host

OpenAI

API key with access to models like GPT-4o

2️⃣ Environment Variables (Recommended)
Set these variables in n8n → Settings → Variables:

SAP_URL=https://<host>:50000/b1s/v1/
SAP_USER=your_username
SAP_PASSWORD=your_password
SAP_COMPANY_DB=your_companyDB

3️⃣ Prepare Google Sheets
Sheet 1: RATE (for charging the data)

Columns: Currency, Rate, RateDate

Sheet 2: LOGS_N8N (to save the logs, success or failed)

Columns: workflow, method, url, json, status_code, message

4️⃣ Activate and Test
Deploy the webhook and grab the URL.

++✅ BONUS++
Built-in AI assistance for input validation and structure

Logs all results for compliance and audit

Flexible integration paths: perfect for hybrid or transitional systems

Nodes used in this workflow

Popular HTTP Request and Microsoft SQL workflows

Flexible Currency Rate Uploads for SAP B1 with AI Validation & Multiple Sources

This workflow automates currency rate uploads into SAP Business One via Service Layer, using flexible input sources such as JSON (API), SQL Server, Google Sheets, or manual values. It leverages logic branching, AI validation, and logging for complete control and traceability. ++⚙️ HOW IT WORKS:++ 🔹 1. Receive Data via Webhook The workflow listens on the endpoint /formulario-datos via HTTP POST. The request body should include: origen: one of JSON, SQL, GoogleSheets, or Manual Depending on the value, the flow branches accordingly. 🔹 2. Authenticate with SAP Business One A POST request is sent to SAP B1’s Login endpoint. A session cookie (B1SESSION) is retrieved and used in all subsequent API calls. 🔹 3. Switch by Origin The flow branches into four processing paths based on origen: JSON: The payload is normalized using OpenAI to extract an array of rates. Each rate is sent to SAP individually after parsing. SQL: The SQL query provided in the payload is executed on a connected Microsoft SQL Server. The results are checked by AI to validate the date format. If valid, rates are sent to SAP. GoogleSheets: Rates are pulled from a connected spreadsheet. Each entry is sent to SAP in sequence. Manual: Uses currency, rate, and rateDate directly from the webhook payload. Sends the result directly to SAP. 🔹 4. AI-Powered Enhancements (Optional but enabled) Normalize JSON: Uses OpenAI (LangChain node) to convert any messy structure into a uniform array under the key rate. Date Formatting: Another OpenAI call ensures RateDate is in yyyyMMdd format (required by SAP), converting from ISO, timestamp, or other formats. 🔹 5. Send to SAP Business One (Service Layer) All paths send a POST request to: /SBOBobService_SetCurrencyRate With a payload such as: { "Currency": "USD", "Rate": "0.92", "RateDate": "20250612" } 🔹 6. Log Results All success/failure results are appended to a Google Sheets log (LOGS_N8N) The log includes method, URL, sent payload, status code, and message. ++🛠 SETUP STEPS:++ 1️⃣ Create Required Credentials: Go to Credentials > + New Credential and configure: SAP Business One (Service Layer) Type: HTTP Request Auth or Token Base URL: https://<your-host>:50000/b1s/v1/ Provide Username, Password, and CompanyDB via variables or fields Google Sheets OAuth2 connection to a Google account with access Microsoft SQL Server SQL login credentials and host OpenAI API key with access to models like GPT-4o 2️⃣ Environment Variables (Recommended) Set these variables in n8n → Settings → Variables: SAP_URL=https://<host>:50000/b1s/v1/ SAP_USER=your_username SAP_PASSWORD=your_password SAP_COMPANY_DB=your_companyDB 3️⃣ Prepare Google Sheets Sheet 1: RATE (for charging the data) Columns: Currency, Rate, RateDate Sheet 2: LOGS_N8N (to save the logs, success or failed) Columns: workflow, method, url, json, status_code, message 4️⃣ Activate and Test Deploy the webhook and grab the URL. ++✅ BONUS++ Built-in AI assistance for input validation and structure Logs all results for compliance and audit Flexible integration paths: perfect for hybrid or transitional systems

Build your own HTTP Request and Microsoft SQL integration

Create custom HTTP Request and Microsoft SQL workflows by choosing triggers and actions. Nodes come with global operations and settings, as well as app-specific parameters that can be configured. You can also use the HTTP Request node to query data from any app or service with a REST API.

Microsoft SQL supported actions

Execute Query
Execute an SQL query
Insert
Insert rows in database
Update
Update rows in database
Delete
Delete rows in database
Use case

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FAQs

  • Can HTTP Request connect with Microsoft SQL?

  • Can I use HTTP Request’s API with n8n?

  • Can I use Microsoft SQL’s API with n8n?

  • Is n8n secure for integrating HTTP Request and Microsoft SQL?

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