Today, most businesses are creating apps that work on smartphones. Most people, including youngsters, are always glued to their mobile screens, so it is apt to introduce apps for business proliferation. However, just creating any ABC app without proper tech stack research can result in technical issues.
A poorly designed app can push prospects away from you. So, how do you think that you will capture the interest of your target market, with so much competition around? Well! There are a lot many solutions that app development companies have on offer for you. But, there is one thing that demands your complete focus. It is the backend development.
Before you get down to choosing the best backend database for a mobile app, it is imperative to understand more about it. What is the backend database?
The backend is the part of the application, which is responsible for storing and processing all the data. What you see in front of the screen is of aesthetic value for the user. The pictures, layout, and fonts have to look attractive, to keep users on the page for a long time. The backend mainly comprises servers, APIs, and databases. Your choice of backend database will depend on the goal of your app.
You should also know about the main components of the backend.
The server is mainly the brain behind the program. It receives requests from the user interface, processes them, and sends the responses back. The server also performs the function of mediating the actions between the app and any outside APIs that are required to perform a certain task.
The data related to the users, content, and the configuration that the app needs to function properly, is located in the database. It facilitates various functions like access and modification and also ensures that the data is available for the app all the time. It also ensures data accuracy, offering a scalable way to grow along with growing volumes of data.
These establish the connection between the mobile apps and the servers. Thus, ensuring a continuous flow of data between the app and the server. It helps in enhancing the app’s functionality and performance.
Developers responded what database they use
Source: Statista
SQL databases are relational database management systems that store data in structured tables with rows and columns. They use Structured Query Language (SQL) for querying and managing data. SQL databases ensure data integrity through ACID properties (Atomicity, Consistency, Isolation, Durability) and support transactions for reliable data manipulation. Common examples include MySQL, PostgreSQL, Microsoft SQL Server, and Oracle Database. These databases are widely used for various applications such as web development, enterprise systems, and data analytics due to their reliability, scalability, and standardized querying language.
Popular SQL based databases are:
MySQL is one of the most well-known SQL databases in the market today. It is the most common one used for mobile apps. According to Statista, In 2022, 46.85% of software developers reported using MySQL, which makes it the most popular database tool.
MySQL is a widely used relational database management system known for its reliability and performance. As a development expert, MySQL offers robust features for efficient data storage, retrieval, and management.
Developers leverage its scalability and compatibility with various programming languages to build versatile applications across industries. For example, an e-commerce platform may utilize MySQL to store product information, customer data, and transaction records, ensuring seamless operations and effective data analysis to enhance user experience and drive business growth.
PostgreSQL, often referred to as Postgres, is an advanced open-source relational database management system renowned for its extensibility, reliability, and adherence to SQL standards. With a rich feature set, including support for complex queries, transactions, and data integrity, PostgreSQL is favored by developers for mission-critical applications.
Its extensibility allows users to add custom functions, data types, and indexing methods, catering to diverse use cases. Moreover, PostgreSQL's commitment to open-source principles fosters a vibrant community and frequent updates. From small-scale projects to enterprise-level deployments, PostgreSQL excels in scalability and performance. For instance, an enterprise resource planning (ERP) system may leverage PostgreSQL's robustness to manage vast amounts of data efficiently while ensuring data consistency and security.
SQLite is a lightweight, self-contained, serverless, and open-source relational database management system widely acclaimed for its simplicity, portability, and efficiency. Designed to be embedded into applications, SQLite requires minimal configuration and operates directly on disk files.
It supports standard SQL syntax and offers features like transactions, triggers, and indexes, making it suitable for small to medium-scale applications, especially in environments with limited resources. For instance, mobile apps, web browsers, and IoT devices often leverage SQLite for local data storage and manipulation. Its small footprint and ease of integration make it an ideal choice for scenarios where a full-fledged database server is unnecessary or impractical, ensuring seamless data management within applications while maintaining performance and reliability.
Microsoft SQL Server is a powerful relational database management system (RDBMS) developed by Microsoft, known for its scalability, security, and comprehensive feature set. It supports transactional processing, business intelligence, and analytics, making it suitable for a wide range of applications.
SQL Server integrates seamlessly with Microsoft's ecosystem, offering tight integration with tools like Visual Studio and Azure services. For example, in an enterprise setting, SQL Server might be employed to manage a large-scale customer relationship management (CRM) system. It enables efficient data storage, retrieval, and complex querying, ensuring businesses can derive valuable insights from their data. With features like Always On Availability Groups and robust security measures, SQL Server provides a reliable foundation for critical business applications.
NoSQL databases are non-relational databases designed to handle large volumes of unstructured or semi-structured data. Unlike SQL databases, they do not require a fixed schema, allowing for more flexibility in data storage. NoSQL databases use various data models, including document-oriented, key-value, wide-column, and graph databases, catering to diverse use cases. They are commonly used in modern web applications, real-time analytics, and big data processing, offering scalability, high availability, and performance for handling dynamic and rapidly evolving data sets.
Some Popular NoSQL databases are:
MongoDB is a leading NoSQL document-oriented database renowned for its flexibility, scalability, and ease of use. It stores data in flexible JSON-like documents, enabling developers to store, retrieve, and manipulate data more intuitively. With dynamic schemas, MongoDB accommodates evolving data structures without requiring predefined schemas, making it ideal for agile development and rapid iteration.
For example, a content management system might utilize MongoDB to store various types of content, such as articles, images, and user comments, in a single collection, facilitating efficient retrieval and updates. MongoDB's distributed architecture and built-in horizontal scaling support ensure seamless scalability to handle large-scale applications and high volumes of data.
Its rich query language, indexes, and aggregation framework empower developers to perform complex queries and analytics, unlocking valuable insights from diverse data sets. Overall, MongoDB empowers developers to build robust, scalable applications with ease.
Redis is a high-performance, open-source, in-memory data structure store known for its speed, versatility, and simplicity. It functions as both a cache and a database, supporting various data types such as strings, hashes, lists, sets, and sorted sets.
Redis is widely used for caching frequently accessed data, session management, real-time analytics, pub/sub messaging, and as a backend for applications requiring high-speed data access. Its lightweight nature and low-latency operations make it an excellent choice for use cases where performance is critical.
For example, a social media platform might use Redis to store user session data, cache frequently accessed posts, and implement real-time notifications. Redis's persistence options, replication, and clustering capabilities ensure data reliability and scalability, making it a popular choice for building scalable, real-time applications that demand high throughput and low latency.
Amazon DynamoDB is a fully managed NoSQL database service offered by Amazon Web Services (AWS). It is designed to handle large-scale, mission-critical workloads with seamless scalability and high throughput, making it suitable for applications requiring predictable performance and low latency.
DynamoDB stores data in tables with flexible schema designs, supporting both key-value and document data models. Its built-in features, such as automatic scaling, multi-region replication, and on-demand capacity, ensure high availability and reliability without the need for manual intervention.
For example, a gaming company might use DynamoDB to store player profiles, game states, and in-game transactions, ensuring fast and reliable access to game data for millions of concurrent players worldwide. With its pay-per-request pricing model and integration with other AWS services, DynamoDB offers a cost-effective and scalable solution for a wide range of applications, from gaming and e-commerce to IoT and mobile backends.
Firebase is a comprehensive mobile and web application development platform provided by Google, offering a suite of services to streamline app development, improve user engagement, and scale applications effortlessly. Central to Firebase is its real-time NoSQL database solutions, including the Firebase Realtime Database and Cloud Firestore.
These databases enable developers to store and synchronize data in real-time across multiple clients, facilitating collaborative and interactive app experiences. Additionally, Firebase offers authentication, cloud messaging, hosting, analytics, and more, all seamlessly integrated into a unified platform.
It is essential for you to choose the right database for the backend application. Its choice will guide the app development and performance later on. So, here are a few important considerations for you.
You first need to understand the type of data that you will be storing and using. The structure of the data is also worth mentioning. The various kinds of data that you will be dealing with on a regular basis are relational data, documents, graphs, or a combination of all of these. If you can identify the kind of data, you can also ascertain the database model which is just right for your needs.
The scalability factor is also worth your consideration. In the beginning, it is important for you to project how many users will be using your app. Can the existing database support that number? There are a few databases that can be scaled horizontally and a few that can be scaled vertically. You need to find out what your requirements and goals are, to get the best database model.
If using a particular database, you have to take into consideration the development cost and time. It should also have the requisite development tools, so that you can work with them in future, too. If not, you must find out what additional software or hardware you need in the coming times, as the number of app users increases. You ought to choose a database that aligns with your goals.
The security of your app data is of prime importance. Apart from that, you also need to make sure that the user’s data is safe. Your chosen database should be able to provide strong security features. It should come with encryption, access control, and authentication features. You might also want to check for compliance as per industry norms.
You may also have to check if your current team has the expertise to handle the database that you are choosing. If you do not have the flexibility to learn and relearn, then stick to the knowledge base present. If you are ready for some extra investment in terms of hiring or training, you can experiment with other databases.
You also need to check how nicely the database integrates with the other tools, that you will be using. Compatibility will lessen the development time and maintenance time as well. You must also check for strong community support.
Consider your data modelling requirements, and how the database handles them. Understand the querying needs to identify the database type
These are a few factors that you must consider before choosing a backend database.
Check also:
Many mobile apps work offline and need the internet to save local data. Take the example of Dropbox, where you can edit and create new files, even when offline. When you connect to the internet, syncing takes place. Choose a database, which provides sync services. Couch base, which is NoSQL, can help in such cases.
Multi-layer models in apps have fields dependent on others. It can be difficult to manage data in such types of apps. If you use something unstructured like MongoDB, it will bring in flexibility.
When SQL databases encounter network issues, they send error messages instead of transferring the data. You may have to re-configure it later. Choosing a database that can resist connection loss is better.
Your database should be able to handle additional load, with the expansion of users. Multithreading is a feature that comes useful. It allows the scheduling of multiple tasks. Distributed databases are better in such cases.
When you need to send notifications for new databases, some changes are needed on the local server. You should be able to add new fields to the local databases. Choosing SQLite as it can work fine, in such cases.
When modifying the same data on multiple devices, conflicts may arise. So, the database needs to have the ability to resolve such conflicts. Flexibility with respect to conflict resolution is very important.
This feature of the database allows simultaneous access, without blocking any threads or other processes. MVCC allows the reader to change the data, while simultaneously writing the changes.
It can be utilized to improve the performance of the app. The feature should allow suggestions to the app users, based on their behavior. The feature can allow the data to be cached locally, without the users logging in. MongoDB is quite proficient in this.
This is another feature of the backend database, which is desirable. It is crucial for real-time apps and games. Replication of the database is one of the numerous ways a backend can reduce latency. Some databases with low latency are MongoDB Realm and Amazon DynamoDB, to name a few.
This is another practice, which reduces the load on the servers. A caching layer can handle numerous requests with low latency. This is a practice that Amazon uses. Redis is one database that suits the purpose.
So, if you are looking for a backend database, then these are the things that you need to look into. Mobile apps keep on changing, according to the business environment. That is why it needs to be highly flexible. Determine the right database for your app, after learning about the attributes and syncing them with your app goals. This will yield the best results.
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