Amazon S3 CSV File Connector for UiPath In this article you will learn how to integrate Amazon S3 CSV File data in UiPath without coding in just a few clicks (live / bi-directional connection to Amazon S3 CSV File). Amazon S3 CSV File Connector can be used to read CSV Files stored in AWS S3 Buckets. Using this you can easily integrate AWS S3 CSV File data. It's supports latest security standards, and optimized for large data files. It also supports reading compressed files (e.g. GZip /Zip).. Using Amazon S3 CSV File Connector you will be able to connect, read, and write data from within UiPath. Follow the steps below to see how we would accomplish that. Download Documentation The driver mentioned above is part of ODBC PowerPack which is a collection of high-performance Drivers for various API data source (i.e. REST API, JSON, XML, CSV, Amazon S3 and many more). Using familiar SQL query language you can make live connections and read/write data from API sources or JSON / XML / CSV Files inside SQL Server (T-SQL) or your favorite Reporting (i.e. Power BI, Tableau, Qlik, SSRS, MicroStrategy, Excel, MS Access), ETL Tools (i.e. Informatica, Talend, Pentaho, SSIS). You can also call our drivers from programming languages such as JAVA, C#, Python, PowerShell etc. If you are new to ODBC and ZappySys ODBC PowerPack then check the following links to get started. ODBC PowerPack - System Requirements and Installation Getting Started - Using ODBC PowerPack ODBC API Driver Help File

Connect to Amazon S3 CSV File in other apps Connect to Amazon S3 CSV File in SSIS Connect to Amazon S3 CSV File in SQL Server Connect to Amazon S3 CSV File in Power BI Connect to Amazon S3 CSV File in SSRS Connect to Amazon S3 CSV File in Informatica Connect to Amazon S3 CSV File in MS Access Connect to Amazon S3 CSV File in MS Excel Connect to Amazon S3 CSV File in SSAS Connect to Amazon S3 CSV File in C# Connect to Amazon S3 CSV File in Python Connect to Amazon S3 CSV File in JAVA Connect to Amazon S3 CSV File in Tableau Connect to Amazon S3 CSV File in SAP Crystal Reports Connect to Amazon S3 CSV File in Azure Data Factory (Pipeline) Connect to Amazon S3 CSV File in Azure Data Factory (SSIS) Connect to Amazon S3 CSV File in Talend Studio Connect to Amazon S3 CSV File in PowerShell Connect to Amazon S3 CSV File in ODBC

Create ODBC Data Source (DSN) based on ZappySys Amazon S3 CSV Driver

Step-by-step instructions

To get data from Amazon S3 CSV File using UiPath we first need to create a DSN (Data Source) which will access data from Amazon S3 CSV File. We will later be able to read data using UiPath. Perform these steps:

1. Install ZappySys ODBC PowerPack.

2. Open ODBC Data Sources (x64):
   

3. Create a User Data Source (User DSN) based on ZappySys Amazon S3 CSV Driver

   ZappySys Amazon S3 CSV Driver

   
   You should create a System DSN (instead of a User DSN) if the client application is launched under a Windows System Account, e.g. as a Windows Service. If the client application is 32-bit (x86) running with a System DSN, use ODBC Data Sources (32-bit) instead of the 64-bit version.

4. Create and configure a connection for the Amazon S3 storage account.

   

5. You can use select your desired single file by clicking [...] path button.

   mybucket/dbo.tblNames.csv

   dbo.tblNames.csv

   
   
   
   ----------OR----------

   You can also read the multiple files stored in Amazon S3 Storage using wildcard pattern supported e.g. dbo.tblNames*.csv.
   

   Note: If you want to operation with multiple files then use wild card pattern as below 
   (when you use wild card pattern in source path then system will treat target path as folder regardless you end with slash)
   
   mybucket/dbo.tblNames.csv (will read only single .CSV file)
   mybucket/dbo.tbl*.csv (all files starting with file name)
   mybucket/*.csv (all files with .csv Extension and located under folder subfolder)
   

   mybucket/dbo.tblNames*.csv

   
   
   
   ----------OR----------

   You can also read the zip and gzip compressed files also without extracting it in using Amazon S3 CSV Source File Task.

   mybucket/dbo.tblNames*.gz

   

6. Navigate to the Preview Tab and let's explore the different modes available to access the data.
   

   1. --- Using Direct Query ---

      Click on Preview Tab, Select Table from Tables Dropdown and select [value] and click Preview.
      

   2. --- Using Stored Procedure ---

      Note : For this you have to Save ODBC Driver configuration and then again reopen to configure same driver. For more information click here.
      

      Click on the Custom Objects Tab, Click on Add button and select Add Procedure and Enter an appropriate name and Click on OK button to create.
      

      1. --- Without Parameters ---

         Now Stored Procedure can be created with or without parameters (see example below). If you use parameters then Set default value otherwise it may fail to compilation)
         
         

      2. --- With Parameters ---

         Note : Here you can use Placeholder with Paramters in Stored Procedure.
         Example : SELECT * FROM $ WHERE OrderID = '<@OrderID, FUN_TRIM>' or CustId = '<@CustId>' and Total >= '<@Total>'
         

         

   3. --- Using Virtual Table ---

      Note : For this you have to Save ODBC Driver configuration and then again reopen to configure same driver. For more information click here.
      

      ZappySys APi Drivers support flexible Query language so you can override Default Properties you configured on Data Source such as URL, Body. This way you don't have to create multiple Data Sources if you like to read data from multiple EndPoints. However not every application support supplying custom SQL to driver so you can only select Table from list returned from driver.

      Many applications like MS Access, Informatica Designer wont give you option to specify custom SQL when you import Objects. In such case Virtual Table is very useful. You can create many Virtual Tables on the same Data Source (e.g. If you have 50 Buckets with slight variations you can create virtual tables with just URL as Parameter setting).

      vt__Customers
      DataPath=mybucket_1/customers.csv
      
      vt__Orders
      DataPath=mybucket_2/orders.csv
      
      vt__Products
      DataPath=mybucket_3/products.csv
      

      1. Click on the Custom Objects Tab, Click on Add button and select Add Table and Enter an appropriate name and Click on OK button to create.
         
      2. Once you see Query Builder Window on screen Configure it.
         
      3. Click on Preview Tab, Select Virtual Table(prefix with vt__) from Tables Dropdown or write SQL query with Virtual Table name and click Preview.
         

7. Click OK to finish creating the data source

8. That's it; we are done. In a few clicks we configured the to Read the Amazon S3 CSV File data using ZappySys Amazon S3 CSV File Connector

Read Amazon S3 CSV File data in UiPath Studio (workstation)

Here we will be reading Amazon S3 CSV File data on your workstation. To accomplish that we will create and run UiPath process package locally. Later on, we'll explore how to publish the package to Orchestrator and run it remotely. For now, let's focus on working locally and get started!

1. Open UiPath Studio.
2. Before we really begin the work, make sure UiPath Studio is set as your profile (blue application icon).
3. In case, it is set to UiPath StudioX, you can change it in UiPath StudioX Settings: Simply select UiPath Studio option:
4. Start by creating a new project based on UiPath Process template:
5. Add Run Query activity in Main Sequence box:
6. Click Configure Connection... button to create an ODBC connection:
7. Continue by clicking Connection Wizard:
8. When the window opens, select ODBC-based driver, provider, and then choose ODBC data source:
   AmazonS3CsvFileDSN

   AmazonS3CsvFileDSN

   
   You can also select Use connection string option and use whole ODBC connection string instead. Obtain the connection string by pressing Copy Settings button in your data source configuration.
9. Once you do that, it's time to configure a SQL query:
   Make sure, you enclose the query in double quotes!
10. Proceed by adding a Write CSV activity after Run Query:
    In this article we are using Write CSV, but you can freely add any other destination of your choice, e.g. Write DataTable to Excel.
11. Once you do that, configure the added Write CSV, this will write Amazon S3 CSV File data to a CSV file:
12. It's time for fun! Which means it's time for debugging! Just run the package locally to debug:
13. Finally, ensure there are no execution errors!

Run UiPath package using Orchestrator (via robot)

UiPath also offers the ability to execute packages remotely using Orchestrator and a robot. This is achieved by publishing the package to UiPath Orchestrator, installing UiPath Assistant on the remote machine, connecting it to Orchestrator, enabling us to run the package remotely. It may sound complicated at first glance, but further steps will clear things out. Let's not waste our precious time and delve into the details!

Publish process package from UiPath Studio

1. First of all, open the UiPath process package we created in the previous step
2. Set the option that our process package Starts in Background:
3. We are ready to Publish it:
4. Make sure, you publish it to the Shared folder in UiPath Orchestrator Tenant workspace:
5. Finally, success! We are ready for the next step - creating UiPath robot - so we can automate the job:

Create robot in UiPath Orchestrator

1. First of all, let's open UiPath Orchestrator from UiPath Automation Cloud console:
2. It's time to create a robot, which will run unattended packages:
3. But first we have to create a runtime. Choose to host our robot on-premise, not in UiPath infrastructure:
4. Let's move along and Create new machine template, this will create a machine in UiPath Orchestrator:
5. Configure the machine to run in Production environment:
6. We are ready to Create new robot account in the new machine:
7. Let's make our robot to work only on background automations:
8. Continue by selecting newly created robot:
9. Select Shared folder, so that everyone in the team can benefit from it:
   This is the folder where we published our UiPath process package "MyProcess"
10. We are almost done! We are given machine Client ID and Client secret which we will use to connect UiPath Assistant to our created machine in Orchestrator. Let's leave this open for a while and see how we can do it in the next step.

Connect UiPath Assistant to Orchestrator

We are ready to connect UiPath Assistant to the machine we created in Orchestrator. UiPath Assistant will run our package in a remote machine. Let's connect it and give it some work!

1. Connect to a remote machine (where your UiPath process package will be running).
2. Install UiPath Studio there.
3. Then configure ODBC data source:

   If you chose Use user or system data source option in connection configuration, when creating UiPath process package, then create an identical ODBC data source on the same remote machine. Use the same configuration as the one created in your workstation in the first step.

   Use Copy Settings and Load Settings buttons to make your life easier. They will help you to transfer settings between different ODBC data sources.

   If you chose Use connection string option, then you don't have to do anything. However, you still have to install ODBC PowerPack on the remote machine.

4. Continue by opening UiPath Assistant and going to Preferences:
5. Find Orchestrator Settings menu item and click it:
6. And here even bigger fun begins! But fear not, all you have to do is open your web browser window with Client ID & Client secret we obtained in the previous step and simply copy and paste those values into UiPath Assistant. Also, don't forget to configure Orchestrator URL:
7. Finally, we get rewarded for the hard work with the Connected as Unattended status:

Create and run UiPath process in Orchestrator

We are at the finish line! Let's create and run UiPath process. This will execute the package on your remote machine using the UiPath Assistant configured earlier.

1. First of all, open UiPath Orchestrator from UiPath Automation Cloud console.
2. Then proceed by going to Process in Shared folder:
3. Continue by simply clicking on Add process button:
4. Select the process package we created in UiPath Studio:
5. Rest a while, and just hit Next, unless your package has requirements:
6. Then simply hit Create button:
7. But let's not stop here and Start the process by creating a job right away:
8. Use the same Production runtime we created before and hit Start:
9. We've reached the final step! In the CSV destination file or destination of your choice you should see Amazon S3 CSV File data:

Advanced topics

Create Custom Stored Procedure in ZappySys Driver

You can create procedures to encapsulate custom logic and then only pass handful parameters rather than long SQL to execute your API call.

Steps to create Custom Stored Procedure in ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here

1. Go to Custom Objects Tab and Click on Add button and Select Add Procedure:
   

2. Enter the desired Procedure name and click on OK:
   

3. Select the created Stored Procedure and write the your desired stored procedure and Save it and it will create the custom stored procedure in the ZappySys Driver:
   Here is an example stored procedure for ZappySys Driver. You can insert Placeholders anywhere inside Procedure Body. Read more about placeholders here
   

   CREATE PROCEDURE [usp_get_orders]
       @fromdate = '<<yyyy-MM-dd,FUN_TODAY>>'
    AS
       SELECT * FROM Orders where OrderDate >= '<@fromdate>';
   

   
   

4. That's it now go to Preview Tab and Execute your Stored Procedure using Exec Command. In this example it will extract the orders from the date 1996-01-01:
   

   Exec usp_get_orders '1996-01-01';

   
   

5. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC usp_get_orders @fromdate=''1996-07-30''')

   
   

6. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

Create Custom Virtual Table in ZappySys Driver

ZappySys API Drivers support flexible Query language so you can override Default Properties you configured on Data Source such as URL, Body. This way you don't have to create multiple Data Sources if you like to read data from multiple EndPoints. However not every application support supplying custom SQL to driver so you can only select Table from list returned from driver.

If you're dealing with Microsoft Access and need to import data from an SQL query, it's important to note that Access doesn't allow direct import of SQL queries. Instead, you can create custom objects (Virtual Tables) to handle the import process.

Many applications like MS Access, Informatica Designer wont give you option to specify custom SQL when you import Objects. In such case Virtual Table is very useful. You can create many Virtual Tables on the same Data Source (e.g. If you have 50 URLs with slight variations you can create virtual tables with just URL as Parameter setting.

1. Go to Custom Objects Tab and Click on Add button and Select Add Table:
   

2. Enter the desired Table name and click on OK:
   

3. And it will open the New Query Window Click on Cancel to close that window and go to Custom Objects Tab.

4. Select the created table, Select Text Type AS SQL and write the your desired SQL Query and Save it and it will create the custom table in the ZappySys Driver:
   Here is an example SQL query for ZappySys Driver. You can insert Placeholders also. Read more about placeholders here
   

   SELECT
     "ShipCountry",
     "OrderID",
     "CustomerID",
     "EmployeeID",
     "OrderDate",
     "RequiredDate",
     "ShippedDate",
     "ShipVia",
     "Freight",
     "ShipName",
     "ShipAddress",
     "ShipCity",
     "ShipRegion",
     "ShipPostalCode"
   FROM "Orders"
   Where "ShipCountry"='USA'

   
   

5. That's it now go to Preview Tab and Execute your custom virtual table query. In this example it will extract the orders for the USA Shipping Country only:
   

   SELECT * FROM "vt__usa_orders_only"

   
   

6. Let's generate the SQL Server Query Code to make the API call using stored procedure. Go to Code Generator Tab, select language as SQL Server and click on Generate button the generate the code.
   As we already created the linked server for this Data Source, in that you just need to copy the Select Query and need to use the linked server name which we have apply on the place of [MY_API_SERVICE] placeholder.
   

   SELECT * FROM OPENQUERY([MY_API_SERVICE], 'EXEC [usp_get_orders] ''1996-01-01''')

   
   

7. Now go to SQL served and execute that query and it will make the API call using stored procedure and provide you the response.
   

Conclusion

In this article we discussed how to connect to Amazon S3 CSV File in UiPath and integrate data without any coding. Click here to Download Amazon S3 CSV File Connector for UiPath and try yourself see how easy it is. If you still have any question(s) then ask here or simply click on live chat icon below and ask our expert (see bottom-right corner of this page).

Download Amazon S3 CSV File Connector for UiPath Documentation 

More integrations

Other application integration scenarios for Amazon S3 CSV File

SSIS

SQL Server

Power BI

SSRS

Informatica

MS Access

MS Excel

SSAS

C#

Python

JAVA

Tableau

SAP Crystal Reports

Azure Data Factory (Pipeline)

Azure Data Factory (SSIS)

Talend Studio

PowerShell

ODBC

Other connectors for UiPath

Amazon Ads

Amazon MWS

Amazon Selling Partner (SP-API)

Asana

Azure DevOps

Cosmos DB

DropBox

ElasticSearch

FastSpring

Google BigQuery

Google Calendar

Google Drive

Google Sheets

Hubspot

Jira

Mailchimp

ManagedEngine ServiceDesk Plus (Zoho)

Nativo

OData

OneDrive

Outlook Mail (Office 365)

Power BI

ServiceNow

SharePoint Online

Shopify

Smartsheet

Stripe

YouTube

Zendesk

Zoho CRM

Zoho SalesIQ

Zoom

REST API

JSON

JSON File

XML

SOAP

XML File

JDBC-ODBC Bridge

Salesforce

CSV

Amazon S3 JSON File

Amazon S3 XML File

Amazon S3 CSV File

Azure Blob JSON File

Azure Blob XML File

Azure Blob CSV File

FTP/SFTP JSON File

FTP/SFTP XML File

FTP/SFTP CSV File

Build your own Custom API Connector

Download Amazon S3 CSV File Connector for UiPath Documentation

Common Searches: