Dataset Overview

The DataSet object is a central component of ADO.NET, providing an in-memory representation of data. It is a collection of DataTable objects, which in turn contain rows and columns that represent data in a tabular format.

A DataSet can hold multiple related or unrelated tables, allowing you to work with complex data structures without needing to maintain constant connections to the data source. This makes it highly effective for disconnected data scenarios.

Key Features of a DataSet

In-Memory Cache: Stores data locally, enabling faster access and manipulation.
Disconnected Operation: Allows applications to retrieve data, close the connection, and then work with the data. Changes can be reconciled with the data source later.
Multiple Tables: Can contain multiple DataTable objects, representing different tables from a database or other data sources.
Relationships: Supports defining relationships between DataTable objects, mirroring foreign key constraints in relational databases.
Constraints: Allows enforcing data integrity through constraints like unique keys and foreign keys.
Data Views: Provides flexible ways to sort, filter, and navigate through data within a DataTable using DataView objects.

Structure of a DataSet

A DataSet is essentially a container for DataTable objects. Each DataTable has:

Columns: Define the schema of the table, similar to database columns.
Rows: Represent individual records in the table.
Primary Key: A unique identifier for rows within the table.
Relations: Links between tables, enabling navigation across related data.
Constraints: Rules to maintain data integrity.

Example of DataSet Structure:


// Conceptual representation
DataSet myDataSet = new DataSet("MyData");

DataTable customersTable = new DataTable("Customers");
customersTable.Columns.Add("CustomerID", typeof(int));
customersTable.Columns.Add("CustomerName", typeof(string));
customersTable.PrimaryKey = new DataColumn[] { customersTable.Columns["CustomerID"] };

DataTable ordersTable = new DataTable("Orders");
ordersTable.Columns.Add("OrderID", typeof(int));
ordersTable.Columns.Add("CustomerID", typeof(int));
ordersTable.Columns.Add("OrderDate", typeof(DateTime));
ordersTable.PrimaryKey = new DataColumn[] { ordersTable.Columns["OrderID"] };

// Define a relationship
DataRelation relation = new DataRelation("CustomerOrders",
    customersTable.Columns["CustomerID"],
    ordersTable.Columns["CustomerID"]);

myDataSet.Tables.Add(customersTable);
myDataSet.Tables.Add(ordersTable);
myDataSet.Relations.Add(relation);

Working with Data

Data is typically loaded into a DataSet using a DataAdapter (e.g., SqlDataAdapter, OleDbDataAdapter). The DataAdapter handles the filling of the DataSet and the updating of the data source.

Loading Data:


string connectionString = "Your_Connection_String";
using (SqlConnection connection = new SqlConnection(connectionString))
{
    SqlDataAdapter adapter = new SqlDataAdapter("SELECT * FROM Customers; SELECT * FROM Orders;", connection);
    DataSet dataSet = new DataSet("CompanyData");
    adapter.Fill(dataSet);
    // Now you can work with dataSet.Tables["Customers"] and dataSet.Tables["Orders"]
}

Accessing Data:

You can iterate through rows and columns of a DataTable within the DataSet:


DataTable customers = dataSet.Tables["Customers"];
foreach (DataRow row in customers.Rows)
{
    Console.WriteLine($"ID: {row["CustomerID"]}, Name: {row["CustomerName"]}");
}

Tip: While DataSet is powerful, for simpler data access scenarios, consider using DataTable directly or lighter-weight objects like DataReader when you don't need the full disconnected capabilities of a DataSet.

Advantages and Disadvantages

Advantages:

Efficient for disconnected applications.
Can handle complex data structures and relationships.
Provides robust data manipulation capabilities.

Disadvantages:

Can consume significant memory for large datasets.
May introduce overhead for simple read-only operations.
Updates to the data source can be complex to manage.

Understanding the DataSet is crucial for developing robust data-driven applications in ADO.NET, particularly in scenarios where data needs to be manipulated offline or across multiple layers of an application.

Microsoft Docs