Why Document Databases Are Popular Among High-Profile E-commerce Sites

The e-commerce industry has grown in recent years to become the dominant method of shopping globally. With over 5 billion internet users worldwide, Statista puts the value of e-commerce sales in 2025, as exceeding $4.3 trillion. As the number of e-commerce platforms and online customers increases, so does the amount of data that needs to be collected, stored, and organized to provide better customer service.

As we outlined in our post, The Importance Of Data Analytics In Modern Business, we are in an era dominated by information, and the role of data analytics in shaping modern business strategies cannot be overstated. In order to remain competitive, companies must process large volumes of data to uncover trends, patterns, and insights that guide more accurate and efficient decision-making.

In order to effectively use this data, companies must choose the right database. For high-profile e-commerce sites, that means choosing a database that can hold massive volumes of data, scale in line with requirements, and organize the data to provide personalized services. The database that is becoming increasingly popular amongst these high-profile e-commerce sites is the document database.

What is a Document Database?

A document database is a type of NoSQL database. Instead of storing data in fixed rows and columns, like a traditional relational database, document databases use flexible documents to store a wide range of semi-structured and unstructured data. Unstructured data doesn’t have a predefined structure or format, like text, images, audio, emails, and videos.

Approximately 80% of all data collected is unstructured data, which is why databases that can store it, like document databases, are becoming increasingly popular. The document databases store data in field-value pairs, and the values in these pairs can be of various types and structures, including strings, numbers, dates, arrays, or objects. A key advantage of the document database is that the documents can be stored in widely used programming formats like JSON, BSON, and XML.

Why Document Databases Are Popular With High-Profile E-commerce Sites

Below are three reasons high-profile e-commerce sites are implementing document databases.

Product and Customer Management

As mentioned above, document databases can store a wide range of data. For e-commerce stores, this data includes product details, prices and availability, customer names and addresses, customer purchase history, and images and videos. Each product in an e-commerce store will have unique attributes, especially similar products.

High-profile e-commerce stores such as Amazon, Walmart, and Shopify store a wide multitude of products. Document databases are able to effectively organize all these products with different attributes under a single document, making the retrieval much more efficient and allowing e-commerce to use the data for personalization services (see below).

Scalability and Large Volume Loads

The ability to scale horizontally sets a document database apart from a relational database. This means that the database can expand by adding more machines or nodes to the existing system rather than upgrading. The document databases on MongoDB demonstrate how this data model can seamlessly expand to handle large volumes of data without a dip in performance compared to traditional relational databases. This is because relational databases offer no way for developers to partition the database across multiple instances to scale as workloads grow.

High-profile e-commerce stores are always expanding in terms of products and customer numbers. Walmart, which has more than 20,000 stores in 28 countries, generates 2.5 petabytes (or 2,500,000 gigabytes) of data every hour. The e-commerce giant uses NoSQL databases to handle the vast amount of data associated with sales transactions, inventory levels, and supply chain logistics.

Personalization

The way document databases sort and organize data allows high-profile e-commerce sites to offer personalized services that are tailored to their customer’s individual needs. An article on Exploring Database Solutions in E-commerce notes how NoSQL databases, such as MongoDB, are suitable for this because the data for product review is unstructured and can change over time.

By collating the information in the documents, e-commerce sites use data analysis to detect patterns based on previous purchases and viewing history. This, in turn, allows for real-time personalization. The most famous example is Amazon through its “Customers who viewed this also viewed” or “Frequently bought together” suggested products. The site uses its own document database called Amazon DynamoDB to provide these personalization services.

Behind every high-profile e-commerce site is a database that is capable of storing, scaling, and improving the site’s services. To cater to these requirements, high-profile sites are using document databases.