This tutorial walks you through the process of extracting blog posts and comments data from Blogger using the REST API and Zappysys SSIS connectors. In this guide, you will learn how to authenticate with the Blogger REST API, configure a Zappysys REST data source, and load extracted data into SQL Server. This approach eliminates the need for custom code and provides a graphical interface for managing complex API integrations.

Zappysys provides a powerful REST connector that simplifies integrating cloud-based APIs into your SQL Server Integration Services packages. We will demonstrate a practical ETL pattern using ZappySys REST connectivity to extract data from Blogger and load it into SQL Server within SSIS.

Prerequisites

Before you begin, make sure you have the following:

• First, you will need to have SSIS installed
• Secondly, make sure to have SSDT
• Thirdly, access to a Blogger blog with appropriate permissions to read public posts and comments.
• Finally, do not forget to install ZappySys SSIS PowerPack.

Steps

Create/Select a Project in the Google API Console

1. Navigate to the Google API Console.
2. Click on the Project Dropdown at the top bar and either select an existing project or create a new one by clicking CREATE PROJECT.
   

   Google Console – Create or select a project

3. Once the project is set, click ENABLE APIS AND SERVICES.
4. Search for the Blogger API v3 and click ENABLE.
   

   Google Console – Enable Blogger API

5. Return to the main screen and click on the OAuth Consent Screen tab.
6. Select the External user type and click CREATE.
7. Provide the application name, user support email, and developer contact information, then click SAVE AND CONTINUE.
8. Click through the remaining scopes and summary pages (no additional scopes are required for this tutorial), and click SAVE AND CONTINUE on each.
9. Move to the Credentials tab.
10. Click CREATE CREDENTIALS in the top bar, choose OAuth Client ID, select Desktop App as the Application Type, and click Create to obtain your Client ID and Secret.
    

    Google Console – Create credentials

11. Download the credentials JSON file and save it in a secure location on your development machine.

Create the OAuth connection for Blogger

1. Create or select your SSIS project, and open the package.dtsx file.
2. Drag and drop the ZS REST API task from the Toolbox.
3. Inside Connection Manager, right-click and select New connection…
4. Inside the SSIS connectors, select the ZS-OAuth
   
   

   Create a new SSIS OAuth API Connection Manager

5. Select the Google API provider
6. Enter the Client ID and Client Secret you generated in the past step
7. Use Blogger URL scope: https://www.googleapis.com/auth/blogger
8. Generate the token
9. Test the connection to ensure it is working correctly.
10. Click OK to save the connection.
    

    OAuth connection – Blogger API

Get information from a Blog

1. Create a string variable {{User::BlogID}} and enter the ID from the blog you want to get information from.
2. From the SSIS Toolbox, drag the ZS REST API Task onto the Control Flow designer.
3. Double-click the task to open the editor.
4. Select the connection manager you created in the previous step.
5. In the URL Path field, enter: https://www.googleapis.com/blogger/v3/blogs/{{User::BlogID}}/posts
6. Set the HTTP method to GET.
7. Click the Preview tab to test the API connection and view sample data.
8. If the preview is successful, click OK to configure the task.
   

   REST API task – Blogger example

Save the information in a SQL table

1. Drag and drop a Data Flow into the Control Flow and double-click it.
   

   Drag and drop Data flow.

2. In the Data Flow, drag and drop the JSON source, then double-click it to configure it.
   

   SSIS JSON Source – Drag and Drop

3. Use the same configuration as in the REST API task, but first enable the Use credentials option.
4. Enter the URL, select the OAuth connection, and use the Method GET.
5. You can use the filter option to get the object you want to get data from: $.Items[*]
6. Preview the data and click OK to save the configuration.
   

   JSON Source – Blogger Example Request
7. Now drag and drop a destination component. In our case, we will use the Upsert destination component.
   

   SSIS – Data Flow – Drag and Drop Upsert Destination Component

8. Double-click in the Upsert destination component to configure it.
9. Select the Action you want to use.
10. Create or select a database connector.
11. Create or select a table.
12. Use the options Insert or/and Update.
13. Map the column; if the columns have the same name, it will be automatic.
14. Select at least one column for a primary key.
15. Click OK to save the configuration.
    

    Upsert destination – Blogger example

16. Run the package, and you will see the data from Blogger in your database
    

    Blogger – result

Code Examples

Sample REST API Request

Here’s an example of retrieving blog posts using the Blogger REST API:

GET https://www.googleapis.com/blogger/v3/blogs/{blogId}/posts
Authorization: Bearer {access_token}
Content-Type: application/json

Example response:

{
  "kind": "blogger#posts",
  "items": [
    {
      "kind": "blogger#post",
      "id": "7109703471293209437",
      "title": "Getting started with Blogger API",
      "content": "Learn how to integrate Blogger with your applications...",
      "published": "2026-03-15T10:30:00Z",
      "updated": "2026-03-20T14:15:00Z",
      "url": "http://example.blogspot.com/2026/03/getting-started.html",
      "author": {
        "displayName": "John Doe"
      }
    }
  ]
}

SQL Table Structure

Recommended table structure for storing Blogger posts data:

CREATE TABLE BloggerPosts (
    PostID BIGINT PRIMARY KEY,
    BlogID BIGINT NOT NULL,
    Title NVARCHAR(MAX),
    Content NVARCHAR(MAX),
    AuthorName NVARCHAR(255),
    PublishedDate DATETIME,
    UpdatedDate DATETIME,
    PostURL NVARCHAR(MAX),
    CreatedDate DATETIME DEFAULT GETDATE(),
    ModifiedDate DATETIME DEFAULT GETDATE()
);

Conclusion

You have successfully learned how to use Zappysys SSIS connectors to extract data from the Blogger
platform using the REST API. With ZappySys SSIS PowerPack, connecting Blogger to your SQL Server becomes
straightforward and reliable. By configuring the REST connector for Blogger and using the native SSIS destination,
you can build a robust ETL pipeline for extracting blog data.

Explore the full capabilities of the ZappySys SSIS PowerPack to optimize your data integration
tasks. By applying this pattern, you can extend your solution to include additional transformations, data
validation, error handling, and scheduling through SQL Server Agent.

Need Help?

If you encounter any issues, our support team is here to help:

1. Live Chat — Use the chat widget (bottom-right corner of this page)
2. Email — support@zappysys.com
3. Support Center — Visit the ZappySys Support Portal

The post SSIS tutorial: How to connect Blogger with SSIS appeared first on ZappySys Blog.

In our previous blog we saw how update / insert data into SQL Server using SSIS Upsert Destination. In this post we will look at specific example on Data migration from Access to Amazon Redshift using SSIS Upsert Destination (Insert, Update, Delete), along with few other topics such as how to create table using Upsert Destination. how to read all Customers data from Ms Access Table and Merge it in the Amazon Redshift.

We will go through the steps to read data from Access and Load into Amazon Redshift.

In nutshell, this post will focus on how to read access table data in SSIS.

So let’s get started.

Requirements

1. First, you will need to have SSIS installed
2. Secondly, make sure to have SSDT
3. Thirdly, do not forget to install ZappySys SSIS PowerPack
4. Finally, Make sure that Microsoft Access installed.

How to Read MS Access table data and migrate that data in Amazon Redshift table.

Let´s start with an example. In this article we will see Data migration from Access to Amazon Redshift.

1. First of All, Drag and drop Data Flow Task from SSIS Toolbox and double click it to edit.
   

   Drag and Drop : SSIS Data Flow Task from SSIS Toolbox

2. Furthermore, drag and drop the OLE DB Source.
   

   OLE DB Source – Drag and Drop

3. Double click on OLE DB Source for configure it and click on New Connection and configure connection as below to connect access database and click on OK.
   

   OLE DB : Access Connection

4. Now in OLE DB Source Select the mode as Table or View and select Preview to view the access table data.
   

   OLE DB Source Preview

5. Now drag and drop Upsert Destination (Insert, Update, Delete) and create connection with Amazon Redshift Database.
   

   Upsert Destination : Amazon Redshift Connection

6. Now select Action as Sync and check all the checkboxes Insert, Update and Delete from target if not found in source. Select the table and Map all the columns and select the Key field(s) and click on OK.
   

   Upsert Destination Configuration

7. That’s it we are ready to migrate MS access table data into Amazon Redshift Table. Execute the package and it will migrate the data.
   

   Upsert Destination (Insert, Update, Delete)

Bulk Update data in Amazon Redshift

So in previous example we saw bulk update or insert (Upsert) in Redshift Table. Now let’s look at how to update data in target table if record exists.

Here is how you can perform bulk update in Amazon Redshift using Upsert Destination.

1. Double click on Upsert Destination for configure it.
2. Set Action Bulk Update => based on matching records on target. Select Connection and Target Table. Click on Map All to Mappings all columns and check on Only Primary Key columns.
   
3. Thats all, Click on OK to save Upsert Destination settings UI.

Bulk Delete data in Amazon Redshift

Here is how you can bulk delete data in Amazon Redshift.

1. Double click on Upsert Destination for configure it.
2. Set Action Bulk Delete => based on matching records on target. Select Connection and Target Table. Click on Map All to Mappings all columns and check on Only Primary Key columns.
   
3. Thats all, Click on OK to save Upsert Destination settings UI.

Conclusion

In this article, we show how to read MS Access table data and migrate the data in Amazon Redshift table using SSIS. We show how to do connect access MS Access using OLE DB Source. Also, we show how to write Sync Insert, Update and Delete in target if not found in Source Using ZS Upsert Destination. If you liked this article and you want to try, you can download the SSIS PowerPack from here (includes 70+ Components).

References

• ZappySys SSIS installer.
• Help File: Upsert Destination

The post Merge / Upsert data in Amazon Redshift using SSIS appeared first on ZappySys Blog.

In our previous blog we saw How to perform Upsert (Update or Insert) for SQL Server Table. In this post we will look at specific example on How to Load data into PostgreSQL – Upsert using SSIS Upsert Destination (Insert, Update, Delete), along with few other topics such as how to create target table using Upsert Destination, how to read data from Ms Access Table and Merge into PostgreSQL using SSIS.

We will go through the steps to read data from Access and Load into PostgreSQL – Upsert in SSIS.

In nutshell, this post will focus on how to read access table data in SSIS.

So let’s get started.

Requirements

1. First, you will need to have SSIS installed
2. Secondly, make sure to have SSDT
3. Thirdly, do not forget to install ZappySys SSIS PowerPack
4. Finally, Make sure that Microsoft Access installed.

Read MS Access data and Upsert into PostgreSQL table

Let´s start with an example. In this article we will see Data migration from Access to PostgreSQL.

1. First of All, Drag and drop Data Flow Task from SSIS Toolbox and double click it to edit.
   

   Drag and Drop : SSIS Data Flow Task from SSIS Toolbox

2. Furthermore, drag and drop the OLE DB Source.
   

   OLE DB Source – Drag and Drop

3. Double click on OLE DB Source for configure it and click on New Connection and configure connection as below to connect access database and click on OK.
   

   OLE DB : Access Connection

4. Now in OLE DB Source Select the mode as Table or View and select Preview to view the access table data.
   

   OLE DB Source Preview

5. Now drag and drop Upsert Destination (Insert, Update, Delete) and create connection with PostgreSQL Database.
   

   Setup SSIS Upsert Destination for PostgreSQL data load (Bulk Update, Insert, Delete)

6. Now select Action as Sync and check all the checkboxes Insert, Update and Delete from target if not found in source. Select the table and Map all the columns and select the Key field(s) and click on OK.
7. That’s it we are ready to migrate MS access table data into PostgreSQL Table. Execute the package and it will migrate the data.

Conclusion

In this article, we show how to read MS Access table data and migrate the data in PostgreSQL table using SSIS Upsert Destination. We show how to do connect access MS Access using OLE DB Source. Also, we show how to write Sync Insert, Update and Delete in target if not found in Source Using ZS Upsert Destination. If you liked this article and you want to try, you can download the SSIS PowerPack from here (includes 70+ Components).

References

• ZappySys SSIS installer.
• Help File: Upsert Destination

The post Load data into PostgreSQL – Upsert using SSIS (Bulk Update, Insert, Delete) appeared first on ZappySys Blog.

In our previous blog, we saw how to export a REST API to MS Access using a VBA Command Button. In this post, we will look at a specific example of data migration from Access to SQL Server using the SSIS Upsert Destination (Insert, Update, Delete), along with a few other topics, such as how to create a table using the Upsert Destination. How to read all the customer data from the MS Access Table and merge it into the SQL Server.

We will go through the steps to read data from Access and load it into SQL Server.

In a nutshell, this post explains how to read data from an Access table in SSIS.

So let’s get started.

Requirements

1. First, you will need to have SSIS installed
2. Secondly, make sure to have SSDT
3. Thirdly, do not forget to install ZappySys SSIS PowerPack
4. Finally, make sure that Microsoft Access is installed.

How to read MS Access table data and migrate that data to a SQL Server table.

Let´s start with an example. In this article, we will see Data migration from Access to SQL Server.

1. First of all, drag and drop the Data Flow Task from the SSIS Toolbox and double-click it to edit.
   

   Drag and Drop SSIS Data Flow Task from SSIS Toolbox
2. Furthermore, drag and drop the OLE DB Source.
   

   OLE DB Source – Drag and Drop
3. Double-click the OLE DB Source to configure it. Click New Connection, configure the connection as shown below to connect to the Access database, and click OK.
   

   OLE DB Access Connection
4. Now, in the OLE DB Source, set the mode to Table or View, and select Preview to view the table data.
   

   OLE DB Source Preview
5. Now drag and drop Upsert Destination (Insert, Update, Delete), and create a connection to a SQL Server Database.
   

   Upsert Destination SQL Server Connection
6. Click the New Table button in the Target Table, change the table name, and click OK to create the table in SQL Server.
   

   Upsert Destination Create Table
7. Now select Action as Sync and check all the checkboxes: Insert, Update, and Delete from the target if not found in the source. Map all the columns and select the Key field(s) and click on OK.
   

   Upsert Destination Configuration
8. That’s it, we are ready to migrate the MS Access table data into the SQL Server Table. Execute the package, and it will migrate the data.
   

   Upsert Destination (Insert, Update, Delete)

Conclusion

In this article, we show how to read data from an MS Access table and migrate it to a SQL Server table using SSIS. We show how to connect to MS Access using an OLE DB Source. Also, we show how to write Sync Insert, Update, and Delete in the target if not found in the Source Using ZS Upsert Destination. If you liked this article and want to try it, you can download the SSIS PowerPack here (includes 70+ Components).

References

• ZappySys SSIS installer.
• Help File: Upsert Destination

The post Data migration from Access to SQL Server using SSIS Upsert Destination appeared first on ZappySys Blog.

In this release we focused on fixing some bugs with Dynamics CRM Source , Dynamics CRM Destination and Reporting Services Task.

Version 2.9.6.10621 [Jun 24, 2019]

New Features/Improvements

• NEW: Excel Source – Add option to read from any sheet by number rather than hard coded table name (e.g. $4$ , $5$ … )

Bug fixes

• FIX: Dynamics CRM Destination – Timeout property is ignored – You may get error – The request channel timed out while waiting for a reply after 00:00:59. Increase the timeout value passed to the call to Request or increase the SendTimeout value on the Binding
• FIX: Dynamics CRM Source – Virtual Fields not included in output or they are NULL
• FIX: General – Sometimes you may see blank OAuth Screen (If error occurred behind the scene)
• FIX: Reporting Services Task – LastStatus field not updated
• FIX: Reporting Services Task – Local report file throws dll load error at run time
• FIX: Reporting Services Task – You may get error on Save UI – Concurrency violation: the UpdateCommand affected 0 of the expected 1 records
• FIX: Salesforce Source – You may get NULL for related Object fields
• FIX: Upsert Destination – When you select all columns as Key – You may get error – Incorrect syntax near the keyword ‘WHEN’

The post SSIS PowerPack v2.9.5 released (Maintenance Release) appeared first on ZappySys Blog.

In this release we focused on mainly focused on fixing high priority bugs related to Upsert Destination. We also added High DPI Monitor Support with Auto Scale UI option (4K Resolution now supported)

Full Notes: https://zappysys.com/onlinehelp/ssis-powerpack/scr/release-notes.htm

Version 2.9.2.10321 [Mar 21, 2019]

New Features/Improvements

• NEW: Excel Source – Add Option to read first sheet and last sheet rather than fixed name ( $last_sheet$ and $first_sheet$ )
• NEW: General – Support for UI Auto Scaling when High DPI / Font Scaling Enabled on your OS (e.g. Win10) – 4K Monitors or High Resolution Display now supported
• NEW: Generator Tarnsforms / Export Tasks for JSON, XML, CSV – Add Option to set Date Format at column level rather than global option
• NEW: Upsert Destination – Add Create Table Option based on Upstream Metadata
• NEW: Upsert Destination – Add option to preview exising data from selected table
• NEW: Upsert Destination – Add option to show source and target column datatypes

Bug fixes

• FIX: All Source Components – After Sorting Available Columns you may lose Output column renames in the columns grid, also output columns sorted in reverse order
• FIX: All Source Components – After Sorting Columns you cannot remove or add columns from the grid
• FIX: Upsert Destination – Mapped Column status icon is not refreshing after column is mapped
• FIX: Upsert Destination – varchar, char, text datatypes detected as DT_WSTR / DT_NTEXT rather than DT_STR / DT_TEXT
• FIX: Upsert Destination – When you have zero rows in source you may get error – Invalid object name #zappysys_xxxxxx_yyyyyyyy
• FIX: Upsert Destination – When you map to column with scale=zero (e.g. numeric(N, 0)) you may get error on save
• FIX: Upsert Destination – You may get error when you change source column after save – An item with the same key has already been added
• FIX: Upsert Destination – You may get object reference not set error in advanced edit

The post SSIS PowerPack v2.9.2 released (Maintenance Release) appeared first on ZappySys Blog.

In this release we focused on mainly providing high quality and super fast Upsert Destination (Bulk Update, Insert and Delete / Merge) for SQL Server. We also added Salesforce BULK API support for Salesforce Destination.

Full Notes: https://zappysys.com/onlinehelp/ssis-powerpack/scr/release-notes.htm

Version 2.9.0.10210 [Feb 08, 2019]

New Features/Improvements

• NEW: Amazon S3 CSV File Source, FTP, Azure – Add UI validation for connection selection (Do not allow preview if selection is not valid)
• NEW: CSV Destination for Azure, AWS, FTP – Validate for no input columns selected
• NEW: Export CSV File Task – Change default delimiter as comma and add enable QuoteAroundValueIfNeeded option by default
• NEW: General – License Manager command line registration doesnt log errors to file (Command line is useful in ADF – SSIS IR in Azure Data Factory – License Registration in setup script)
• NEW: General – Reduce verbosity of connection not assigned validation error
• NEW: HTML Email Task – Provide an option to prevent HTML Encoding when you insert Recordset Variable (add new placeholder {{User::varRecordset,table_no_encode}} )
• NEW: HTTP Connection Manager – Add option to retain Cookies in Dynamic Token Method (e.g. SAP Odata / SOAP API use case)
• NEW: JSON, XML Source – Provide an option to set CharacterSet / Encoding just like REST API Task (e.g. Support UTF-8 without BOM )
• NEW: Salesforce Destination – Add support for Bulk API for very large dataset
• NEW: Secure FTP Connection – Lower the default minimum Key Size to 512 bit to support old version keys (Some customers reported problem with default 1023 bit size key we forced in last version)
• NEW: Secure FTP Task – Show file size in log
• NEW: Upsert Destination – Bulk Update, Insert, Delete and Merge for SQL Server

Bug fixes

• FIX: Amazon S3 CSV Source – When File name contains colon ( : ) it may not work when you hit preview (You get 404 Error)
• FIX: CSV File Destination – Object reference not set error may be thrown on ReleaseConnection
• FIX: Export JSON File Task, Export XML Task, Export CSV Task- Input string was not in a correct format.Couldn’t store <> in SomeIntegerColumn. Expected type is Int32
• FIX: JSON Generator Transform – Hidden columns with Include in output option may be NULL if Multiple rows included in output document
• FIX: PostgreSql Source, Amazon Redshift Source – License is not validated correctly
• FIX: Salesforce Connection Manager – For long running salesforce JOB you may get session timeout error after 2 hours
• FIX: Secure FTP Connection Manager – You cannot specify Host Key Exchange algorithms, if you set you get server and client has no common algorithm error
• FIX: Secure FTP Connection Manager – You may get error – Negotiation failed. Server signature is not valid
• FIX: Secure FTP Task – Progress event shows counter starting from zero rather than one
• FIX: XML Source, XML Parser Transform – When 2D Transform Enabled , Cannot deal with XSI:NIL or self closing nodes correctly: Type cast exception

SSIS Upsert Destination

In this release we added very useful component for Upsert operation (in SQL Server Database for now). This component can perform High performance Bulk Upsert (Insert + Update) in a single operation. It uses Key based Lookup. You can also do Bulk Delete or Bulk Update.

SSIS Upsert Destination Example – Bulk Insert or Update in SQL Server (Merge Records)

Salesforce BULK Update Feature

We also added highly requested feature in Salesforce to use BULK API for very large dataset. By default Salesforce Destination uses SOAP API for Insert operation. Which is good for most part if you don’t have large dataset. For millions of rows it won’t perform good. This is why we added Bulk API mode.

We added two new properties. EnableBulkApiMode and MaxRowsPerJob. When EnableBulkApiMode is enabled BatchSize is ignored.

SSIS Salesforce Destination – Upload Data using BULK API mode

The post SSIS PowerPack v2.9 released (Upsert Destination, Salesforce BULK API and more…) appeared first on ZappySys Blog.

In our previous post, we saw how to call REST API in SSIS. Now let’s learn how to read data from SAP S4 / HANA OData Service (i.e. S/4HANA). SAP HANA provides an OData REST API interface to access data in your application using HTTP Protocol. We will use the SSIS XML Source component to read SAP data and load it into the SQL Server Table in a few clicks.

About SAP HANA / OData REST API Service

You can expose your SAP Data using ODATA REST API Service. Here is a good article that shows how to expose data as an OData Service. For more information on the SAP OData Service feature check the SAP help page. If you are new to OData standard then read an article to learn more about it. If you need an XML-based OData Service then use the test URLs below:

https://services.odata.org/Northwind/Northwind.svc/
https://services.odata.org/Northwind/Northwind.svc/Customers
https://services.odata.org/Northwind/Northwind.svc/Orders
https://services.odata.org/Northwind/Northwind.svc/Invoices
https://services.odata.org/Northwind/Northwind.svc/Products

Now let’s look at how to read SAP Data in SSIS. At this point, we assume you have exposed your data as OData Endpoint.

Step-by-Step Instructions

Let’s look at the step-by-step approach to how to read SAP data using SSIS components. Then we will load SAP HANA data into SQL Server.

Read SAP HANA data using XML Source

First, let’s look at the steps on how to configure XML Source. We will read data from SAP S4 / HANA OData Service and then we will look at how to load data into SQL Server in the next section.

1. Open an SSIS package.
2. Drag Data Flow Task from SSIS Toolbox and double-click it to open it.
3. From the SSIS Toolbox drag ZS XML Source onto the background of Data Flow (in the designer). Double-click it to open the XML Source configuration window.
4. Change Data Format to OData. Selecting this option will take care of REST API pagination too.
5. Enter your OData Service URL. Its format looks similar to the one shown below. Replace 3 parts with your own value (i.e. replace {MY-INSTANCE}, {MY-PROJECT}, {MY-TABLE}):
   

   https://{MY-INSTANCE}/sap/opu/odata/sap/{MY-PROJECT}/{MY-TABLE}

   For example, if you are hosting SAP HANA in a cloud instance then your URL may look like this:
   

   https://myXXXXXX-api.s4hana.ondemand.com/sap/opu/odata/sap/MyTestProject/PurchaseOrders

6. Check the Use Credentials checkbox and select the New ZS-HTTP Connection option.
7. In HTTP Connection Manager select the Basic Authentication option and enter your SAP HANA UserID / Password.
   

   Configure SSIS HTTP Connection (SAP S4 / HANA OData Service – Using Basic Authentication)

8. Let’s get back to the XML Source connector we created in the previous stage. Press the Select Filter button or directly type

   $.feed.entry[*]

     into the field as shown below:
   

   Select Filter for OData Service (XML REST API)

9. Click Preview to make sure you can see the records.
10. Click OK to save the configuration and close the configuration window.

In the next section, we will configure the target to load SAP data into SQL Server using the ZappySys Upsert Destination Data Flow component.

Load SAP HANA data into SQL Server using Upsert Destination

ZappySys SSIS PowerPack makes it easy to load data from various sources such as REST, SOAP, JSON, XML, CSV or from other source into SQL Server, or PostgreSQL, or Amazon Redshift, or other targets. The Upsert Destination component allows you to automatically insert new records and update existing ones based on key columns. Below are the detailed steps to configure it.

Step 1: Add Upsert Destination to Data Flow

1. Drag and drop the Upsert Destination component from the SSIS Toolbox.
2. Connect your source component (e.g., JSON / REST / Other Source) to the Upsert Destination.

SSIS - Data Flow - Drang and Drop Upsert Destination Component

Step 2: Configure Target Connection

1. Double-click the Upsert Destination component to open the configuration window.
2. Under Connection, select an existing target connection or click NEW to create a new connection.
   • Example: SQL Server, or PostgreSQL, or Amazon Redshift.

Step 3: Select or Create Target Table

1. In the Target Table dropdown, select the table where you want to load data.
2. Optionally, click NEW to create a new table based on the source columns.

Configure SSIS Upsert Destination Connection - Loading data (REST / SOAP / JSON / XML /CSV) into SQL Server or other target using SSIS

Step 4: Map Columns

1. Go to the Mappings tab.
2. Click Auto Map to map source columns to target columns by name.
3. Ensure you check the Primary key column(s) that will determine whether a record is inserted or updated.
4. You can manually adjust the mappings if necessary.

SSIS Upsert Destination - Columns Mappings

Step 5: Save Settings

• Click OK to save the Upsert Destination configuration.

Step 6: Optional: Add Logging or Analysis

• You may add extra destination components to log the number of inserted vs. updated records for monitoring or auditing purposes.

Step 7: Execute the Package

• Run your SSIS package and verify that the data is correctly inserted and updated in the target table.

SSIS Upsert Destination Execution

Conclusion

In this post, we saw how easy it is to read SAP S4 HANA data using XML Source SSIS connector that is part of ZappySys SSIS PowerPack. Download it, try it out, and see it for yourself! It has many more connectors that were not mentioned in this post but could be also very helpful in your daily work.

The post Read SAP S4 / HANA data in SSIS (OData REST API) appeared first on ZappySys Blog.