What are Different Methods to Do Pagination in PostgreSQL?

In the area of database management, PostgreSQL has a diversity of methods to optimally implement pagination traversing over a range of data retrieving needs.

From traditional set-based pagination to very advanced keyset pagination and window functions, PostgreSQL has a wide range of techniques that are accessible by both database administrators and developers to easily process large datasets.

In this article, We will learn about the Different Methods of pagination in PostgreSQL by understanding various methods along with the practical implementation of the method and so on.

What are Different Methods to Do Pagination in PostgreSQL?

• Pagination in PostgreSQL is the procedure that consists of decomposing large data sets into several smaller and more suitable parts for fast retrieval and display of information to the user.
• It serves as the tool where users can get through the numerous results by separating each page to bring the best user experience while optimizing the system performance itself, which also makes it easy for them to find the information they need.
• By using the function of pagination, PostgreSQL is giving a chance to the developers to handle large numbers of data smoothly even the application will respond well.

1. Using Limit and Offset
   
2. Using Keyset Pagination
3. Using Key-Centric Pagination

Let’s set up an Environment

To understand What are Different Methods to Do Pagination in PostgreSQL we need a table on which we will perform various operations and queries. Here we will consider a table called products which contains id, name, price, and category as Columns. After inserting some data into the products, the table looks:

products table

1. Using Limit and Offset

One simple way to paginate in PostgreSQL is by using the LIMIT and OFFSET clauses. LIMIT limits the number of rows returned, and OFFSET skips a specified number of rows before starting to return rows.

In the below example, we will retrieve 10 rows starting from the 21st row (offset of 20).

SELECT id,name, price, category
FROM products  
ORDER BY id
LIMIT 5bOFFSET 0;

Output:

Limit and Offset (output)

Explanation: The resulting line provides the first 5 rows from the product table in ascending order of their IDs. LIMIT keyword constrains the rows here to only 5, and with OFFSET 0 none of the first rows are skipped, the process is like scraping a list from the beginning of the result. As a result, one can find a list with items in this sequence, which has IDs from 1 to 5, followed by names, prices, and categories

2. Using Keyset Pagination (Cursor-based Pagination)

Keyset pagination, also known as cursor-based pagination, relies on using unique keys to navigate through the dataset. It’s especially useful for large datasets where traditional OFFSET pagination becomes inefficient.

SELECT  id,name, price, category
FROM products  
WHERE id> 5
ORDER BY id
LIMIT 10;

Output:

Keyset Pagination (Cursor-based Pagination)

Explanation: The output below demonstrates the next 5 rows from the product table, where the ID column is greater than the 5 element, ordering the record from the ID column ascendingly. In contrast to the present technique that resorts to a constant shift, keyset pagination by now dynamically picks the point where, immediately before, the result is spread to avoid mixing it with the results previously fetched. Here, we define WHERE id> 5 which means that this statement retrieves rows IDs that has greater value than the IDs of the previous retrieved data. However, the result features entities ranging from item ID 6 to 10 and their details.

3. Using Key-Centric Pagination

Similar to keyset pagination, key-centric pagination relies on unique keys but provides more flexibility in navigation by directly using the primary key of the table.

SELECT   id,name, price, category
FROM products
WHERE id > 5
ORDER BY id
LIMIT 5;

Output:

Key-Centric Pagination

Explanation: This output also displays the first 5 rows starting from where the last page ended. By the same token, we use WHERE id > 5 for taking the rest of the rows with IDs above the highest ID of the previously fetched rows. The result set will feature products with identities from 6 to 10, put in ascending order of their IDs, combined with info like product names, prices, and categories. The method enables users to navigate efficiently as it directly uses the primary key of the table as a way of managing the pagination.

Conclusion

Overall, Pagination is a principal functionality of the internet which provides the basis to scale webpage to accomodate big datasets, and PostgreSQL offers three ways to implement it. Although the LIMIT and OFFSET method is true to its word, it proves to be unproductive when working with a big data set. Keyset pagination and key-centric pagination empower scalability by enabling smooth databases and contents flowing non-stop. The arc of the data set, indexing, and application requirements are the factors that play a similar role in the pagination process. Through this comprehension, developers could define pagination strategies in order to keep the performance of PostgreSQL-powered applications optimal and user could experience in a satisfying way.