The days of keeping a big diary with the details of your business and customers are long gone because ecommerce databases have taken up that role. In fact, an ecommerce database is the modern-day version of a shopkeeper's diary. It consists of important information such as catalogs of products available to sell, stock inventory, prices, descriptions, order tracking, and customer details.
These databases are essential for smooth operations, as they act as a structured repository for business and manage crucial data. This guide delves into the essential elements of an ecommerce database, offering insights into its structure, functionality, and the various types available to support your online business.
Key components of an ecommerce database
Several key components make up an ecommerce database. All of them play an equally important role, so let’s take a look at what they are.
#1 Product catalog management
This component consists of all the information related to products offered by your store for sale. More specifically, it includes essential information such as names, descriptions, categories, images, and inventory levels. It helps you keep track of all the products and makes inventory management easier. Organizing this data is crucial to avoid losses due to lost or damaged products. According to ZipDo, poor data management practices can reduce a company’s operational efficiency by 21%.
#2 Order processing and fulfillment
This segment of your database handles the entire product lifecycle, from sitting on the shelf to order processing and fulfillment. To this end, it keeps track of orders placed, items to be delivered, inventory levels (in real-time), invoice generation, delivery logistics, and payment confirmation. It streamlines the ordering and delivery process, avoids mistakes, keeps operations flowing, and boosts customer satisfaction.
#3 User management
User management is also essential because it handles sensitive information about customers who visit and use your website. It encompasses data about the user ranging from basic details like their name, email, passwords, payment options, and preferences. User management could get “messy” at times, as it deals with their personal information, so securing this information with encryption is a must, preferably through 128-bit.
Types of ecommerce databases
The different types of ecommerce databases are relational, non-relational, and hybrid. Essentially, they all serve the same purpose but differ in their features, benefits, and characteristics.
#1 Relational databases
As the name might lead you to believe, relational databases consist of data that are related to each other. These databases store data in tables, rows, and columns like an organized spreadsheet, making it easy to gain valuable insights at a glance.
For example, if your store maintains a customer management and order processing database, it would have interconnected tables such as customers, orders, order details, and shipping.
Customers table: Contains information like customer ID, name, email, password, and address.
Orders table: Records each order made by a customer, with details like order ID, customer ID, order date, total amount, and shipping ID.
Order details table: Contains the exact details of what each order includes, with fields like order ID, product ID, quantity, weight, and price.
Shipping table: Holds shipping-related details, such as shipping ID, order ID, shipping method, cost, and estimated delivery date.
The relational structure allows you to retrieve data efficiently. Examples of relational databases include MySQL, Microsoft SQL Server, PostgreSQL, Azure SQL Database, and Amazon RDS.
#2 Non-relational databases (NoSQL)
Unlike what the name might suggest in this case, non-relational databases can also store related data. Essentially, non-relational databases are flexible, which is ideal if your store has a variety of products with different attributes. For example, a clothing item might have attributes like size, color, and material, while electronic gadgets might have specifications like processor speed, memory size, and connectivity options.
Non-relational databases don’t have a fixed schema like relational databases and aren’t limited to a tabloid form of data arrangement. They are well-suited for organizing unstructured or semi-structured data into various formats, such as graphs, tables, documents, etc.
Examples of non-relational databases (NoSQL) include MongoDB, Couchbase, Cassandra, Amazon DynamoDB, and Azure CosmosDB.
#3 Hybrid databases
Hybrid databases combine relational databases' structure and security features with the flexibility and scalability of non-relational databases. For example, if you’re maintaining a product catalog management database, the relational part will ensure transactional integrity for stock levels and pricing, while the non-relational part will provide flexibility in product metadata and customer reviews.
Hence, hybrid databases leverage the strengths of SQL and NoSQL models and are great for ecommerce businesses with specific requirements and needs. Examples of this database include Couchbase Server, Azure Cosmos DB, and Google Cloud Spanner.
Relational vs non-relational databases
The choice between relational and non-relational databases is an important one. Although the decision may seem complicated, it all boils down to factors such as your scalability requirements, the type of queries and transactions, and the data structure. You can use one of them or both simultaneously.
Let’s compare the two.
#1 Relational database
Relational databases are suitable for transactions and non-product content. They can also be used for most parts of product catalogs.
Here are the pros and cons:
Pros | Cons |
Utilizes a structured data model with predefined schemas. | Structured models might face difficulties when dealing with large-scale applications. |
Contains primary and foreign keys for higher levels of data integrity. | Certain types of relational databases have expensive license fees and maintenance. |
Relational databases like MySQL, PostgreSQL, and Oracle have been extensively used and have great support. | With large data sets and complex queries, sometimes performance bottlenecks are created. |
Transactional reliability is guaranteed, thanks to it being ACID compliant (Atomicity, Consistency, Isolation, Durability). | Involves vertical scaling, which is not the cheapest. |
Being the prime examples of relational databases, let’s look deeper into MySQL and PostgreSQL.
MySQL is an open-source Relational Database Management System (RDBMS) trusted by many for its reliability, performance, and scalability options. It uses several optimization techniques, including indexing, query caching, multiple database sets for fault tolerance, automatic sharding, and replication. Besides having a strong ecosystem, MySQL is compatible with various programming languages.
PostgreSQL is also an open-source relational database management system packed with extensibility and reliability features. It can handle high-level workloads and complex data requirements.
Here’s how it differs from MySQL:
Indexing: PostgreSQL uses different indexing options, such as hash indexes, partial indexes, expression indexes, and trees. These help fine-tune your database’s performance. On the other hand, MySQL uses only B-tree and R-tree.
Data types: MySQL supports numeric, character, date and time, spatial, and JSON data types, while PostgreSQL supports all MySQL data types, as well as geometric, enumerated, network address, arrays, ranges, XML, hstore, and composite. It’s more versatile and easier for database developers to use.
ACID compliance: MySQL is only ACID-compliant under certain circumstances. PostgreSQL is fully ACID-compliant, leading to enhanced data integrity and reliability.
#2 Non-relational database
In addition to transaction history, non-relational databases can be utilized for customer and product data and are a great option for providing personalized experiences to your customers.
Here are the pros and cons of it:
Pros | Cons |
Flexible schemas and design to accommodate new data models. | Limited query capabilities restrict complex reporting and data analysis. |
High-performance and easier to develop. | There’s a learning curve to it. |
Capable of handling large amounts of structured and semi-structured data. | Lack of ACID compliance. |
Designed for horizontal scalability, meaning they are capable of handling high volumes of data and traffic. | Despite increasing usage of NoSQL, its ecosystem is still smaller compared to relational databases, hence the lack of third-party tools, community support, and libraries. |
MongoDB and CouchBase are the most popular examples of non-relational databases, so let's compare them both.
Designed for performance and scalability, MongoDB stores data in documents called BSON. More specifically, it converts JSON data into BSON, the binary representation of a JSON document, and uses a schema-free design. It features powerful capabilities like indexing, text search, geospatial queries, CRUD operations, and more.
It can scale horizontally by distributing data across multiple servers via automatic sharing. Also, it uses a master-slave replication model with primary and secondary nodes for writing and reading.
On the other hand, Couchbase operates on a multi-model support system that works with query-based access patterns, documents, and key values. It features a built-in caching layer, reducing the time it takes to access data.
Moreover, it uses N1QL (pronounced "nickel"), a SQL-like query language designed for JSON data, and allows writers to add queries, joins, and aggregations. It’s designed for businesses looking for a low latency, high performance, and flexible data model capable of dealing with multi-dimensional queries.
Principles of good ecommerce database design
Designing an effective ecommerce database requires careful consideration of several factors, as it is responsible for the smooth functioning of operations and business development.
There are a few key principles to keep in mind, such as the following:
#1 Efficiency
A good ecommerce database design is efficient in performance and responsiveness.
Several factors contribute to it, including:
Maintaining data integrity and minimizing redundancies.
Using cache for faster load times and less stress on the machine, as servers can get overloaded with time.
Using designs that are easy to understand and make the processing of retrieving data easier.
Remember, companies with a strong emphasis on data can see an average annual revenue increase of 5.32% because of better data use. [1]
#2 Scalability
An ecommerce database worth its salt understands that a business aims to grow, so it should have scalability options.
It must be able to:
Scale the database horizontally and vertically and handle increased capacity.
Replicate your data to protect it while partitioning it and organizing it in a way that makes retrieving data convenient.
Apply auto-scaling to scale resources automatically and monitor your database regularly for configuration changes and optimization.
#3 Security
You cannot compromise the security of your database, as it contains very sensitive information. Therefore, the security techniques your ecommerce database utilizes must provide protection against breaches and data loss.
Here are some security practices to follow:
Use encryption and data masking strategies.
Comply with the industry and established government standards.
Monitor and perform audits to check for break-in attempts or data manipulation.
Building your ecommerce database
There are several steps to consider when creating your ecommerce database.
#1 Select your database
Start by evaluating your ecommerce needs, the types of products and services you will offer, scalability requirements, and data volume. You should also consider the complexity of your data structure. Once that’s clear, you need to select a database. As discussed earlier, essentially, two types of databases are available: Relational and Non-Relational, or MySQL or NoSQL databases. Both have pros and cons, so choose the one that best suits your requirements.
#2 Set up your database
Setting up your ecommerce database can be a task that ranges from planning to implementation. Hence, start by planning your database schema. Factors like product catalog, user profiles, inventory management, and more are major. Ensure data integrity and querying efficiency, and use indexing and optimization techniques to boost performance. Once your database is ready, several deployment options are available, such as self-hosting, cloud hosting, or using managed services like Google Cloud SQL, Azure SQL database, or Amazon RDS.
#3 Maintain security and compliance
As also highlighted above, security and compliance are two areas that cannot be ignored when creating and using a database. To ensure you utilize the best possible security practices, it’s recommended to use encryption techniques like SSL/TLS, stay informed about any updates, and regularly perform audits. Importantly, security is especially necessary if you’re just starting out, as according to Small Business Trends reports, 43% of security breaches affect small businesses.
#4 Test and Optimize
Once everything is online, thoroughly test your database, look for issues, and rectify them accordingly. Maintenance is part of the deal, so you must make it a routine to maintain performance and security.
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FAQs
What is an ecommerce database?
An ecommerce database acts as a diary that stores data such as customer information, orders, product information, transaction records, etc. It makes data handling more efficient by centralizing it and making it easy to retrieve.
Which database is best for ecommerce?
The best database for ecommerce is the one that fulfills your specific requirements. Relational databases can be used for structured data, while non-relational databases (NoSQL) are much more flexible, scalable, and capable of handling semi or unstructured data. If you have diverse data needs, opt for NoSQL.
What type of database is used in ecommerce?
Relational, non-relational, and hybrid are the different types of databases used in ecommerce. Relational databases are favored in ecommerce for their structured data organization and robust transactional integrity, which makes them ideal for handling customer and order data. Non-relational (NoSQL) databases offer scalability and flexibility and are suited for varied and evolving ecommerce data. Hybrid databases merge both types, providing structured reliability with scalability and flexibility, catering to diverse ecommerce data management needs efficiently.
Should I use SQL or NoSQL for ecommerce?
The choice between SQL and NoSQL databases depends upon several factors, such as scalability needs, performance expectations, data types and structure, and transaction requirements. However, if you have diverse data needs, opt for NoSQL.