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When dealing with data loads in SQL Server Integration Services (SSIS), it's common to encounter scenarios where the full replacement of the data set is not only inefficient but also unnecessary. This is where incremental load design patterns come into play. Incremental loads, also known as delta loads or change data capture, focus on loading only new or changed records from the source data to the destination. This blog post will focus on some of the most common design patterns for implementing incremental loads in SSIS.

The first pattern to consider is the Changed Data Capture (CDC) feature. This feature, available in SQL Server 2019 and Azure SQL, captures changes made to the source data and allows SSIS to load only those changes. This is particularly useful for large databases, where a full load may take a considerable amount of time. Here's an example of setting up CDC on a table:

-- Enable CDC on the database
EXEC sys.sp_cdc_enable_db;

-- Enable CDC on the table
EXEC sys.sp_cdc_enable_table
@source_schema = N'dbo',
@source_name   = N'YourTable',
@role_name     = NULL,
@supports_net_changes = 1;

Another pattern is the use of a timestamp or date column to track changes. This can be implemented in any relational database management system, including MySQL 8.0 and DB2 11.5. In this approach, each record has a timestamp column that gets updated whenever the record changes. When loading data, SSIS only loads records where the timestamp is later than the last load time. Here's an example of creating a table with a timestamp column in MySQL:

CREATE TABLE YourTable (
  id INT NOT NULL,
  data VARCHAR(100),
  last_modified TIMESTAMP DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
  PRIMARY KEY (id)
);

Azure Synapse Analytics, an analytics service for big data and real-time analytics, supports incremental loads through PolyBase. PolyBase allows you to use T-SQL queries to access and combine both non-relational and relational data. You can set up an external table that points to the source data, then use a T-SQL query to load only the new or changed data.

To summarize, implementing incremental loads in SSIS can increase efficiency and performance by only loading new or changed data. While the specific implementation may vary depending on the technology and specific requirements, the general principles remain the same. By using features like CDC in SQL Server and Azure SQL, timestamp columns in MySQL and DB2, or PolyBase in Azure Synapse, you can implement robust and efficient incremental load strategies in SSIS.