Difference Between Data Reader and Dataset (With Table)

Data Reader and Dataset are used in ASP.NET coding. They are used for binding the data. Dataset is not only used in ASP.NET coding. It is also used in some other projects. In many projects, a dataset acts as a base so that the scraping of data and many other works can be done. A data reader is mainly used for reading and forwarding the data. 

Data Reader vs Dataset

The main difference between Data Reader and Dataset is that Data Reader can provide read-only and forward-only access to data. On the other hand, Dataset has multiple row sets, and it can be from the same data source. Data Reader is bound to one control only. Whereas the dataset is bound to multiple controls. Data Reader is manually coded. The dataset is supported by visual studio tools.

Data Reader contains an easy way for a programmer to read data from a database. It is the solution for forwarding the streaming of data in ADO.NET. For using a data reader, you should first create an instance of the command object. Then, create a data reader by calling the command. It is ideal for quickly retrieving results. Since you cannot create it directly, you should use execute reader command. 

Dataset is a collection of a related set of information. It can be manipulated as a unit by a computer. A simple example of the dataset is the test score of each student in a different class. It is a collection of values or numbers that are related to a particular subject. For each of the variables, it lists values such as height and weight.  

Comparison Table Between Data Reader and Dataset

Parameters of Comparison

Data Reader



It is used to retrieve read-only and forward-only data from the database.

It is a collection of in-memory tables.


It uses a single table.

It uses multiple tables.

Persist data

It cannot persist.

It can persist.

Speed performance

It is better.

It is slower due to overhead.


It is a connected architecture.

It is a disconnected architecture.

What is Data Reader?

It is a broad category of objects used for reading data sequentially from a data source. It has an efficient way of accessing data. It is accompanied by a command object as it contains query, connection object to run the query, and optionally has any parameters. It parses tabular data from a Microsoft SQL Server. It also has other methods of retrieving data from other sources. It produces faster results than a data adapter for returning the same data.

This is because the data adapter also uses a data reader for retrieving the data. It reads data from the database and is a forward and read-only connection-oriented architecture. It is a direct implementation of the record set model that is used in legacy languages like VB6 or VB++. It uses a server-side cursor. In ASP.NET, the data should be combined, and it uses a data reader along with executing reader. When you want to increase the performance by retrieving data as soon as possible, then a data reader should be used. 

Since it is a connection-oriented architecture, you must have a connection to fetch the data from the database. It can use either a strong or weak typing approach for processing the data. If a particular result does not fit well, then stronger typing can cause problems. In that case, people should use weaker typing. With the help of a data reader, developers can modify and access data in relational databases and some other systems. 

What is Dataset?

It is a collection of data. If it is tabular data, then a dataset will have one or more database tables. There are many types of datasets available such as numerical datasets, multivariate datasets, correlation datasets, bivariate datasets, and categorical datasets. The main purpose of the dataset is to avoid direct communication with the database. 

It uses simple SQL statements. It acts as a cheap local copy of the data. So that you don’t have to make expensive, high latency calls to the database. According to AWS datasets, it has three blocks called assets, revision, and datasets. According to excel, it is a range of contiguous cells that contains data to analyze. According to python, it is the basic data container in PyMVPA. It is the primary form of data storage. It also acts as a common container for results that are returned by algorithms. 

In a specific project, they are top-level containers that are used for organizing and controlling access to tables and views. Each feature or column in a dataset represents a measurable piece of data for data analysis. A dataset source is a location where the data is derived. It could be a database, scraped web data, and live measurements from physical devices. 

Main Differences Between Data Reader and Dataset

  1. Data Reader is based on one SQL statement from the database. On the other hand, the dataset can include multiple tables from different databases.
  2. Data Reader uses a single table. On the other hand, Dataset uses multiple tables.
  3. Data readers do not have persistent data. On the other hand, the dataset has persistent data.
  4. Speed performance is better in the data readers. On the other hand, speed performance is better in the dataset.
  5. Data reader is a connected architecture. On the other hand, the dataset is a disconnected architecture.
  6. The data reader has no storage capacity. On the other hand, the dataset has a temporary storage capacity. 


Both Data Reader and Dataset are very useful while using SQL coding in the project. But one thing that should be remembered is that a data reader is executed along with executing reader in the coding. A dataset can have multiple tables with any number of rows and columns. Working with them might be difficult, and one should have proper practice for that. 

It can have a different class with numbers related to that particular subject. Many people prefer data reader because it is a connection-oriented architecture and works with more speed even though it has only a single piece of data. This is because speed will reduce gradually when there are multiple tables involved while working with the project. 


  1. https://arxiv.org/abs/2112.06494
  2. https://arxiv.org/abs/1704.04683