DataReader vs DataSet: A Guide to Connected and Disconnected Data Access 

DataReader and DataSet are two significant data access models that can greatly impact the performance, scalability, and responsiveness of your .NET application.  The connected model, powered by DataReader, keeps a live connection open and streams data forward-only to maximize speed and minimize memory usage. The disconnected model, implemented through DataSet, takes the opposite approach. It loads data into memory so you can edit and reuse it without constant database interaction. 

Among these two, the model you choose affects your application responsiveness, memory consumption, database load, and even how well your system scales under pressure. That’s why data providers like ADO.NET support both approaches, giving you the freedom to optimize for performance or flexibility as needed. 

In this article, we’ll break down DataReader vs. DataSet through the lens of connected and disconnected data access. Let’s get right into it. 

• What is a DataReader? (connected access)
• What is DataSet? (disconnected access)
• Comparing DataReader and DataSet: connected vs disconnected
• Boosting productivity with dotConnect’s visual tools
• Conclusion 

What is a DataReader? (connected access) 

A DataReader is the most lightweight and efficient way to read data in ADO.NET. It uses the connected data access model, which keeps your database connection active while streaming data one row at a time. DataReader comes in handy for scenarios where speed is crucial and data is handled only once in sequence. 

Furthermore, a DataReader provides a forward-only, read-only stream of data from a database. Meaning, once a row is read, you can’t go back, and while the DataReader is open, the database connection remains open as well. 

Key features include: 

• Connected model: Requires an open database connection throughout the read operation.
• Forward-only access: Rows are read sequentially, one at a time.
• Read-only: Data cannot be modified through the DataReader.
• High performance: Minimal memory usage and fast execution.

DataReader is commonly used in high-throughput applications, reporting tools, and services that process large result sets. 

Example: reading data with DataReader 

using System; 
using Devart.Data.PostgreSql; 
 
class Program 
{ 
    static void Main() 
    { 
        string connString = "Host=localhost;Port=5432;Database=sakila;User Id=postgres;Password=yourpassword;License key=**********"; 
         
        using (PgSqlConnection conn = new PgSqlConnection(connString)) 
        { 
            conn.Open(); 
            PgSqlCommand cmd = new PgSqlCommand( 
                "SELECT actor_id, first_name, last_name FROM actor", conn); 
             
            using (PgSqlDataReader reader = cmd.ExecuteReader()) 
            { 
                while (reader.Read()) 
                { 
                    int id = reader.GetInt32(0); 
                    string firstName = reader.GetString(1); 
                    string lastName = reader.GetString(2); 
                    Console.WriteLine($"{id}: {firstName} {lastName}"); 
                } 
            } 
        } 
    } 
} 
 
 

Explanation 

• PgSqlConnection establishes a live connection to the PostgreSQL database.
• PgSqlCommand executes the SQL query against the database.
• PgSqlDataReader retrieves the result set and iterates through it row by row.
• The Read() method moves the cursor forward, processing each row sequentially. 

This approach is efficient because data is streamed directly from the database, processing one row at a time without loading the entire result set into memory. 

Pros and cons of DataReader 

Pros 

• Very fast and lightweight.
• Minimal memory consumption.
• Ideal for large result sets.
• Simple and predictable execution flow.

Cons 

• Requires a continuously open database connection.
• No support for backward navigation.
• No built-in data manipulation or relationships.
• Less suitable for data binding and complex business logic.

DataReader is particularly effective when performance is crucial and data needs to be consumed sequentially, one time only.  

What is a DataSet? (disconnected access) 

A DataSet represents the disconnected data access model in ADO.NET. Instead of keeping a constant connection to the database, a DataSet retrieves data, stores it in memory, and allows the application to work with it independently. This approach makes it especially useful for complex data manipulation, data binding, and scenarios where maintaining an open connection is inefficient. 

Additionally, a DataSet is an in-memory, relational representation of data. It closely mirrors a mini database inside your application and is composed of several key components: 

• DataSet: the container that holds one or more DataTables and their relationships.
• DataTable: this represents a table of data with rows and columns.
• DataRow: represents a single record within a DataTable.
• DataRelation: defines relationships between DataTables (similar to foreign keys).

Together, these components allow a DataSet to model complex data structures, enforce constraints, and track changes without requiring a live database connection. 

Example: using DataSet and DataAdapter with dotConnect

using System; 
using System.Data; 
using Devart.Data.PostgreSql; 
 
class Program 
{ 
    static void Main() 
    { 
        string connString = "Host=localhost;Port=5432;Database=sakila;User Id=postgres;Password=yourpassword;License key=**********"; 
         
        using (PgSqlConnection conn = new PgSqlConnection(connString)) 
        { 
            PgSqlDataAdapter adapter = new PgSqlDataAdapter( 
                "SELECT * FROM actor", conn); 
 
            PgSqlCommandBuilder builder = new PgSqlCommandBuilder(adapter); 
 
            DataSet ds = new DataSet(); 
            adapter.Fill(ds, "actor"); 
 
            DataTable actorTable = ds.Tables["actor"]; 
 
            foreach (DataRow row in actorTable.Rows) 
            { 
                Console.WriteLine($"{row["actor_id"]}: {row["first_name"]} {row["last_name"]}"); 
            } 
 
            // Insert new row 
            DataRow newActor = actorTable.NewRow(); 
            newActor["first_name"] = "John"; 
            newActor["last_name"] = "Doe"; 
            actorTable.Rows.Add(newActor); 
 
            adapter.Update(ds, "actor"); 
            Console.WriteLine("New actor inserted."); 
        } 
    } 
} 
 
 

Explanation 

• PgSqlDataAdapter retrieves data from the database and fills the DataSet.
• PgSqlCommandBuilder automatically generates INSERT, UPDATE, and DELETE commands.
• The DataSet stores the actor table entirely in memory.
• A new DataRow is added to the DataTable without an active database connection.
• adapter.Update() synchronizes in-memory changes back to the database. 

The DataSet model allows you to manipulate data freely and push changes to the database only when needed. 

Pros and cons of DataSet 

Pros 

• Works without a persistent database connection.
• Supports complex data relationships and constraints.
• Enables insert, update, and delete operations.
• Ideal for data binding, caching, and offline scenarios. 

Cons 

• Higher memory consumption compared to DataReader.
• Slower for large result sets. 
• More complex architecture.
• Overhead may be unnecessary for simple, read-only operations. 

DataSet is best suited for scenarios where flexibility, rich data manipulation, and disconnected access outweigh raw performance concerns.  

Comparing DataReader and DataSet: connected vs disconnected 

The key distinction between DataReader and DataSet is the connected and disconnected data access, which directly affects performance, memory usage, scalability, and how your application interacts with data. The table below provides further comparisons between the two. 

When to use DataReader and DataSet 

Use DataReader when: 

• You need maximum performance and minimal memory usage.
• Data is read-only and processed sequentially.
• You’re working with large result sets.
• The operation is short-lived, and connection usage is controlled. 

Use DataSet when: 

• You need disconnected access to data.
• Your application performs insert, update, or delete operations.
• You’re working with multiple tables or relationships.
• Data will be bound to UI components or cached.
• Scalability and flexibility are higher priorities than raw speed. 

In summary, DataReader prioritizes speed and simplicity, while DataSet prioritizes flexibility and richer data interaction. Understanding this significant difference is essential for building efficient, scalable .NET applications. 

Boosting productivity with dotConnect’s visual tools 

Although DataReader and DataSet are effective frameworks for defining how you access data, tools like dotConnect make the process quicker and more efficient. dotConnect includes vital visual tools you can use to transfer repetitive and error-prone tasks into design-time tooling, allowing you to focus on application logic rather than boilerplate code, especially when working with DataSets and data-bound applications.  

Let’s break down these dotConnect’s visual tools. 

DataSet wizard 

The DataSet wizard helps you to quickly create strongly typed DataSets using a visual, guided workflow. Instead of manually defining schemas and tables, configuring relationships, and writing DataAdapter code, the wizard automates these tasks for you. In just a few steps, it generates a fully configured DataSet that is complete with tables, columns, and adapters, ready to be used immediately in your application. To use the DataSet wizard, follow the steps below: 

1. Launch the DataSet Wizard from the Visual Studio designer.

2. Select a dotConnect data provider and configure the database connection. 

3. Choose tables, views, or custom SQL queries. 

4. Review and customize column mappings and schema settings. 

5. Generate the strongly typed DataSet and associated DataAdapter logic. 

Once generated, the wizard creates: 

• Typed DataTables and DataRows
• Preconfigured DataAdapters
• Ready-made methods for Fill and Update operations 

DataSet wizard comes in handy if your team works with large schemas or frequently changing databases. 

DataSet manager 

The DataSet manager complements the DataSet wizard by providing a centralized way to maintain and evolve your DataSet over time. It helps you to edit table schemas and column properties, define and manage DataRelation objects, configure constraints and keys, and adjust data bindings without rewriting code 

The DataSet Manager is especially useful in WinForms and other data-bound scenarios, where UI components depend heavily on consistent schemas and relationships. Instead of touching multiple files, you can manage the entire DataSet structure from a single visual interface. 

Together, the DataSet Wizard and DataSet Manager feature in dotConnect turn DataSet-based development into a visual, maintainable, and scalable workflow. For applications that rely on disconnected data access, complex schemas, or UI binding, these tools significantly shorten development time while reducing the risk of runtime errors. 

Conclusion 

DataReader and DataSet are both effective data access models; however, they differ in functionality and applicable scenarios. DataReader excels at speed and efficiency, providing a lightweight, forward-only method for reading data while keeping an open database connection. In contrast, DataSet prioritizes flexibility when handling in-memory data, including updates, relationships, and offline scenarios, at the expense of higher memory usage and overhead. 

As such, DataReader is ideal for high-performance, read-only operations, while DataSet is the best option in data-intensive applications requiring editing, data binding, or interaction with numerous connected tables. Choosing the proper model leads to improved performance, scalability, and maintainability. To make the right choice, your best solution is dotConnect. By fully supporting both connected and unconnected models, dotConnect allows you to optimize each data access scenario without changing tools or providers. Whether you need improved speed with DataReader or rich data manipulation with DataSet, dotConnect adapts to your requirements. 

To accelerate development and reduce errors, use dotConnect’s design-time tools, including the DataSet Wizard and DataSet Manager. These tools simplify schema design, DataAdapter generation, and connection management, enabling you to build your data access layer faster and with greater reliability.