It’s pretty challenging to pick the best when we have many options. The same happens with mobile app developers. They find it hard to choose the right database for an app.
Here, the right database means the most suitable database that assists in building a mobile app and updating an existing one. The mobile app database determines if your app holds the caliber to handle multiple users (old or new) and regular maintenance and updates.
This post will discuss the criteria for choosing the right database, top mobile app databases, and more. We ensure this blog will give you what you want when picking the right mobile app database.
Let’s start!
Table of Contents
A mobile app database is an organized collection of well-structured information according to the app’s needs.
The databases are housed electronically on a desktop or laptop and managed, edited, and updated utilizing database management systems (DBSM). The combination of the DBMS, the stored information, and the app all associatively makes a database system, or, we can say, a database.
The data is stored in the database as rows and columns, making data management and processing fast and easy.
Besides an obvious requirement of a database, there are other needs of databases also.
The everyday use of a database is to store a large amount of data better. Let’s know about some more usages.
Mobile app databases ensure ultimate data security from hacking and theft. DBMS arrives with various user logins, and new users need permission to access the database every time.
The information that app databases store is highly dependable as DBMS comes with a checking system that identifies errors that need removal.
Developers can quickly search through mobile app databases using Data Query Language (DQL).
DBMS includes Data Manipulation Languages (DML), which ensure timely and seamless updates of the app database.
You may find it surprising that mobile app databases are of different types. Let’s find out.
When the data is stored across distinct physical locations in a database, it’s distributed. It can be located in various computers placed in the exact physical location or scattered over a network of interconnected computers.
A database where data is stored in a “center” spot is a centralized database. Here, the “center” location states the database is saved in a single place but can be accessed from any external resource.
For instance, When you have complete data on your work PC, you will have easy access to it from your personal PC if that database is centralized.
Cloud-based database apps perform in the cloud. Such apps are a great innovation as they have a large amount of space to house data. The cloud is the technology over the internet that functions as a centralized database as it is always available, and one can access it from anywhere.
NoSQL is the only type of database that works uniquely from all other application databases . General mobile app databases store data in rows and columns patterns , but NoSQL arrives with a flexible schema that permits a developer to house data in various shapes and sizes.
Organizations that run on enterprise-based database apps need an extensive database to house employee information.
Here arrive commercial app databases. These provide login controls and ample storage to ensure data security.
When we enter our personal details on any social media page or online shopping site, that information is saved on the end-user database. Also, if you have seen the cookies we accept while browsing websites, the databases store cookies that help personalize your online experience.
The whole process occurs in the background and doesn’t disturb user information.
The growing firms always try to create relationships between two or more app databases. This is known as relational data, and a relational database eases handling such sort of data.
The data is stored in rows and columns in this app database, making it easy to build relationships between databases.
Let’s Build A New App Together
Let’s now check out some popular top databases in developing Android and iPhone apps. You can choose the best one for your apps based on their needs.
An open-source and free native multi-model database system, ArangoDB supports three data models with a unified query language, AQL, and one database core.
Written in: C++, JavaScript
Apache CouchDB is an open-source document-oriented database using various formats and protocols to transfer, store, and process its data.
Written in: C, JavaScript, C++,
A database that helps build and run successful apps is Firebase. It is supported by Google and preferred by app development companies, from startups to global enterprises. Furthermore, it’s a cross-platform API with minimal needs for setup. And one can access it easily as a real-time database from his mobile device.
An open-source, free, distributed document-oriented database, RethinkDB stores JSON documents with dynamic schemas and is best for pushing real-time updates for query results to apps.
Written in: Java, Python, JavaScript, C++
A lighter version of the popular MySQL database, SQLite is an embedded app database that permits developers to provide mobile phone users the local data storage.
Written in: C
An open-source database, Realm is developer-friendly and an alternative to SQLite and CoreData. It starts in minutes, ports the app in hours, and saves work for weeks.
Written in: Swift, Objective-C, Java, Kotlin, C#, and JavaScript.
A commercially supported fork of the MySQL relational DBMS, MariaDB, is intended to stay open-source and free software.
Written in: C, C++, Perl
A source-available cross-platform database-oriented database program, MongoDB uses JSON-like documents with operational schemes.
Written in: JavaScript, Python, Java, PHP, C, C++, Ruby, Perl
A fully managed proprietary NoSQL database service, Amazon DynamoDB supports document and key-value data structures. It helps in building modern apps at any scale with high performance.
A unique relational database, PostgreSQL is the best database for Android and iOS apps. Developers can customize this database as they want; that’s why it’s the most preferred mobile app database.
Written in: C
A distributed NoSQL cloud database, Couchbase delivers exceptional versatility, scalability, financial value, and performance across on-premises, cloud, edge computing, distributed cloud, and hybrid deployments.
Written in: C++, Erlang, C, Go, Java
A distributed NoSQL key-value data store, the Riak DB, provides high availability, operational simplicity, fault tolerance, and scalability.
Written in: Erlang
An open-source time-series database, InfluxDB stores and retrieves time series data in fields.
Written in: Go
An open-source and free, wide-column, distributed store, Apache Cassandra is a NoSQL DBMS that handles vast amounts of data across various commodity servers.
Written in: Java
A general-purpose distributed memory caching system, Memcached is best for speeding up dynamic database-driven websites by caching data and objects in RAM.
Written in: C
An in-memory data structure store, Redis is used as an in-memory, distributed, cache, key-value database, and message broker.
Written in: C
An open-source relational DBMS, MySQL is a fully managed database service used to deploy cloud-native apps.
Written in: C, C++
Also called a Sybase SQL Server, SAP Adaptive Server is a relational model database that offers availability and high performance to process targeted transactions. It lowers the operational cost of app development with a relational database server. Besides, it deploys on infrastructure as a service (IaaS) and on-premise.
Written in: C, C++
A blazing-fast, popular, and open-source platform, Solr is developed on Apache Lucene. It’s highly scalable, reliable, and fault-tolerant, offering distributed indexing, automated failover and recovery, replication and load-balanced querying, and more.
Written in: Java
It is powered by AI and developed for deeper insights. It can be available anywhere through the IBM Cloud Pak for the Data. It combines an AI-infused, proven, enterprise-ready data management system with AI and an integrated data platform developed on the scalable, security-rich Red Hat OpenShift foundation.
Written in: C, C++, assembly, Java
It’s the world’s top workplace innovation platform that helps customize apps and automate workflows. You can develop custom apps to streamline manual processes, create new efficiencies, and reduce costs using its low-code.
An open-source non-relational distributed database, Apache HBase offers real-time, random read/write access to your Big Data. It’s an open-source, versioned, distributed, non-relational database model.
Written in: Java
A column-oriented, in-memory, relational DBMS, SAP HANA performs like the software running a database server to store and retrieve data as the apps request.
Written in: C, C++
A multi-model DBMS, Oracle is best for online transaction processing, mixed database workloads, and data warehousing.
Written in: Assembly language, C, C++
Dedicated to storing data securely, Splunk adheres to global and industry compliance initiatives. It’s an advanced database technology required that uses indexing to search and address the stored log files.
A DBMS that merges the relational Microsoft Jet Database Engine with a GUI and software-development tools, Microsoft Jet Database Engine is a venture from Microsoft.
A free, distributed, and open search and analytics engine, Elasticsearch is developed on Apache Lucene. It’s a central component of the Elastic Stack, a set of open and free tools for enrichment, data ingestion, analysis, storage, and visualization.
Written in: Java
A database service provider, Teradata offers database and analytics-relevant products, software, and services. It’s best for enterprise analytics and is a connected multi-cloud data platform that unifies everything.
It’s a managed cloud database that runs on a cloud computing platform. It is a fully managed platform as a service (PaaS) database engine that manages many database management functions, like patching, upgrading, monitoring, and backups with no user involvement.
A data warehouse software project, Apache Hive offers an SQL-like interface to query the data stored in any database and file systems integrated with Hadoop. It is crafted to handle petabytes of data quickly using batch processing. Moreover, it is easy to scale and distribute based on your requirements.
Written in: Java
A relational DBMS, Microsoft SQL Server is a software product that is primarily used to store and retrieve data as the software apps request. It’s is best at managing information.
Written in: C, C++
An open-source NoSQL DBMS, OrientDB is a multi-model database, supporting document, graph, value/key, and object models. It combines the strength of graphs and the flexibility of documents into a high-performing and scalable operational database.
Written in: Java
A graph DBMS, Neo4j, offers data scientists and developers the most advanced and trusted tools to develop intelligent apps and ML workflows. It’s available as a self-hosted and fully managed cloud service.
Written in: Java
A lightweight ORM library for java apps, ORMLite offers standard features of an ORM tool for the general use cases with no added complexity and overhead of any ORM frameworks.
Written in: Java
An open-source SQL relational DBMS, Firebirdsql runs on Microsoft Windows, Linux, macOS, and many Unix platforms.
Written in: C++
A software library, Berkeley DB offers a high-performance embedded database for value/key data. Also, it provides a simple function-call API for data management and access.
Written in: C
Various criteria assist in picking a suitable database for your mobile apps.
The structure points out the way you want to store and retrieve your data. Mobile apps deal with data in different formats.
Offline applications store entire data on mobile devices, whereas Online applications rely on server access to let the store data function.
The data size is the data quantity that you want to store and retrieve as crucial app data. The amount of data may vary according to a combination of chosen data structure, the caliber of database to differentiate data across various file systems and servers.
So, you should pick a mobile database considering the entire volume of data generated by an app at any particular time and the data size you want to retrieve from the database.
Before selecting a mobile app database, you need to perform data modeling as suggested by experts. It’s a representation of data structures that you want to store in the database and robust expression of the business needs.
Data modeling is best when your app holds features, such as reporting, search queries, location-based features, and more. Such mobile apps need various databases to handle distinct sorts of data.
For instance, Uber uses various databases, like MongoDB, MySQL, etc. such databases help it store a high amount of incoming data.
Scale and speed let us know the time incoming reads and writes to your app, demand to service. Some databases assist in optimizing read-heavy applications, while others are best to support write-heavy solutions.
Choosing a database with the caliber to handle an app’s I/O requirements leads to a scalable architecture.
For instance, MongoDB may be faster than MySQL to handle a large volume of unstructured data, but the latter is faster for structured data.
While using decentralized and synchronized storage, it’s essential to securely transmit, access, and store data. For this, you would address authentication, data in motion, data at rest, and read/write access.
Authentication needs to be flexible and permit the use of public, standard, and custom authentication providers. For data at rest on the client and server, you need support for data-level encryption and file system encryption. Communication needs to carry over a secure channel for data in motion, such as TLS or SSL.
If you are planning to make apps for one or more platforms and thinking of deciding later, then you should consider them now.
Today, various mobile apps are emerging to add a native desktop app or a web app. So, you should also think in this direction.
If you want to develop mobile applications for Android and iOS platforms, you can use the React Native framework. It would be easier to build for both platforms simultaneously, as the developers hold the caliber to share code on both mobile app development platforms. Moreover, it supports all sorts of databases.
Now, let’s check out the selection criteria as per the use cases:
Many apps that hold a multi-layer data model are tough to manage data as the “fields and tables” stay dependent on one another.
Also, various apps change over time and demand alterations and modifications in the database structure.
If you choose a structured database, like PostgreSQL, you will fail to make changes frequently.
So, selecting an unstructured database, such as MongoDB, you would find it flexible to modify.
Many apps come with features that allow them to perform offline but demand an internet connection to store local data to the application’s server.
For instance, Dropbox facilitates editing and crafting new files even in offline mode. And when you go online, the changes get synced to the cloud.
So, choose the app database that can allow automatic local database sync to the cloud server and vice-versa, like Couchbase.
While scaling your app, you think of appending more resources as servers that lead to an efficient database.
The database needs to be multi-threaded according to which it should hold the caliber to use the resources and manage the parallel processing.
Multithreading facilitates a database to schedule the parallel jobs on the current resources and reduce the workload on the server-side.
Furthermore, you should also have a distributed database to split the services on varied threads to decrease the workload of the main database. This leads to improved parallel processing of databases.
A mobile app that changes the same data on various devices simultaneously may end up with conflicts. The database should always be supportive of conflict resolution mechanisms. It’s essential and should permit resolution automatically in the cloud, on the device, by a human, or an external system.
While transferring the required data, if the network connection of any SQL database disconnects from the client-side storage, it leads to an error message. And if it happens frequently, it may demand database re-configuration.
So picking a database that provides better reliability and doesn’t lose connection frequently is better in this case.
If we want to update our mobile app, it will demand some modifications to the local database. So, developers should stay updated with old database versions.
The database you select should facilitate the addition of new tables and fields and handle old APIs and database structures for the users who have the latest app version.
We Have The Means To Get You There
Let’s now check out the best practices to consider for working with mobile app databases.
Such a method permits simultaneous access with no interference in processes or threads.
MVCC facilitates a reader to check data snapshot before the writers make changes by permitting read and write operations parallelly.
| Database | MVCC |
|---|---|
| Firebird | Yes |
| MongoDB | Yes |
| Realm | Yes |
| MySQL | Partially, when used with XtraDB |
| MariaDB | Partially, when used with XtraDB |
| RethinkDB | Yes |
| InformixDB | Yes |
| PostgreSQL | Yes, but inefficient |
| MemBase | Yes |
It is best to improve the mobile app’s performance by looking at when, how, and where users use your app. Based on their behavioral traits, you can identify the users’ segment and serve them with specific information they always want.
You can cache and make data available locally before the users log in to your unique app ideas. You can also pick MongoDB as it offers predictive caching that permits developers to serve the users with predictive-cached data before they ask for it.
We should append a caching layer to decrease the servers’ load. Moreover, we need to cache data on this caching layer to avoid a recurring request for the same data. This lowers the number of requests approaching the server and makes the server’s performance more efficient.
For example, mobile apps like Amazon receive various recurring requests. One can decrease the server’s load by appending the caching layer. It holds the caliber to manage millions of requests with the lowest latency. You can also use Memcached and Redic for such needs.
Low latency is vital for online gaming and real-time apps. High latency gives the app users the wrong impression . Anything that moves down from 500ms is a high latency.
So, you can follow any method to reduce the replication and latency of the database. Moreover, you can choose databases with, on average lower latency:
Choosing a database is an important decision as it may lead to the making or breaking of your app. You need to check whether your chosen mobile app database fits the abovementioned criteria.
We hope this post gives you what you expect about mobile app databases and finding a flexible one.
If you want to create a mobile app, hire the best app development company with skilled iOS and Android developers who can turn your app ideas into reality.
Author Amit Samsukha
CTO at Emizentech and a member of the Forbes technology council, Amit Samsukha, is acknowledged by the Indian tech world as an innovator and community builder. He has a well-established vocation with 12+ years of progressive experience in the technology industry. He directs all product initiatives, worldwide sales and marketing, and business enablement. He has spearheaded the journey in the e-commerce landscape for various businesses in India and the U.S.
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