Query Sage 300 Data as a SQL Server Database in Node.js

You can use CData Connect AI to query Sage 300 data through a SQL Server interface. Follow the procedure below to create a virtual database for Sage 300 in Connect AI and start querying using Node.js.

CData Connect AI provides a pure MySQL, cloud-to-cloud interface for Sage 300, allowing you to easily query live Sage 300 data in Node.js — without replicating the data to a natively supported database. As you query data in Node.js, CData Connect AI pushes all supported SQL operations (filters, JOINs, etc) directly to Sage 300, leveraging server-side processing to quickly return Sage 300 data.

Configure Sage 300 Connectivity for NodeJS

Connectivity to Sage 300 from NodeJS is made possible through CData Connect AI. To work with Sage 300 data from NodeJS, we start by creating and configuring a Sage 300 connection.

1. Log into Connect AI, click Sources, and then click Add Connection

2. Select "Sage 300" from the Add Connection panel

3. Enter the necessary authentication properties to connect to Sage 300.

   Sage 300 requires some initial setup in order to communicate over the Sage 300 Web API.

   • Set up the security groups for the Sage 300 user. Give the Sage 300 user access to the option under Security Groups (per each module required).
   • Edit both web.config files in the /Online/Web and /Online/WebApi folders; change the key AllowWebApiAccessForAdmin to true. Restart the webAPI app-pool for the settings to take.
   • Once the user access is configured, click https://server/Sage300WebApi/ to ensure access to the web API.

   Authenticate to Sage 300 using Basic authentication.

   Connect Using Basic Authentication

   You must provide values for the following properties to successfully authenticate to Sage 300. Note that the provider reuses the session opened by Sage 300 using cookies. This means that your credentials are used only on the first request to open the session. After that, cookies returned from Sage 300 are used for authentication.

   • Url: Set this to the url of the server hosting Sage 300. Construct a URL for the Sage 300 Web API as follows: {protocol}://{host-application-path}/v{version}/{tenant}/ For example, http://localhost/Sage300WebApi/v1.0/-/.
   • User: Set this to the username of your account.
   • Password: Set this to the password of your account.
   
4. Click Save & Test
5. Navigate to the Permissions tab in the Add Sage 300 Connection page and update the User-based permissions.

Add a Personal Access Token

When connecting to Connect AI through the REST API, the OData API, or the Virtual SQL Server, a Personal Access Token (PAT) is used to authenticate the connection to Connect AI. It is best practice to create a separate PAT for each service to maintain granularity of access.

1. Click on the Gear icon () at the top right of the Connect AI app to open the settings page.
2. On the Settings page, go to the Access Tokens section and click Create PAT.
3. Give the PAT a name and click Create.
4. The personal access token is only visible at creation, so be sure to copy it and store it securely for future use.

With the connection configured and a PAT generated, you are ready to connect to Sage 300 data from Node.js.

Query Sage 300 from Node.js

The following example shows how to define a connection and execute queries to Sage 300 with the SQL Server module. You will need the following information:

• server: tds.cdata.com
• port: 14333
• user: a Connect AI user (e.g. [email protected])
• password: the PAT for the above user
• database: The connection you configured for Sage 300 (Sage3001)

Connect to Sage 300 data and start executing queries with the code below:

var sql = require('mssql')
var config = {
	server: 'tds.cdata.com',
	port: 14333, 
	user: '[email protected]', //update me
	password: 'CONNECT_USER_PAT', //update me	
	options: {
		encrypt: true,
		database: 'Sage3001'
	}
}

sql.connect(config, err => { 
    if(err){
        throw err ;
    }
    new sql.Request().query('SELECT * FROM OEInvoices', (err, result) => {
        console.dir(result)
    })
        
});

sql.on('error', err => {
    console.log("SQL Error: " ,err);
})