Last Updated on April 25, 2022

It’s pretty challenging to pick the best when we have a plethora of options. The same happens with mobile app developers also. They find it hard to choose the right database for an app. 

Here, the right database means the best 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 that this blog will give you what you want when picking the right mobile app database. 

Let’s start!

What Is A Mobile App Database?

An organized collection of well-structured information according to the app’s needs is a mobile app database. 

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. 

In the database, the data is stored as rows and columns that make data management and processing fast and easy. 

What Is The Need For Mobile App Databases?

Besides an obvious requirement of a database, there are other needs of databases also. 

Read on!

The everyday use of a database is to store a large amount of data in a better way. Let’s know about some more usages. 

Data Security

Mobile app databases ensure ultimate data security from hacking and theft. DBMS arrives with various user logins, and every time the new users need permission to access the database. 

Pointing Out Errors

The information that app databases store is highly dependable as DBMS comes with a checking system that points out errors that need removal.

Easy & Fast Search

Developers can quickly search through mobile app databases using Data Query Language (DQL). 

Hassle-Free Updates

DBMS includes Data Manipulation Languages (DML), which ensure timely and seamless updates of the app database. 

Types Of Mobile App Databases

You may find it surprising to know that mobile app databases are of different types. Let’s find out.

Distributed Database

Distributed Database

When the data is stored across distinct physical locations in a database, it’s a distributed database. It can be located in various computers placed in the exact physical location or scattered over a network of interconnected computers. 

Centralized Database

Centralized Database

A database where data is stored in a “center” spot, it’s 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 the complete data on your work PC, you will have easy access to it from your personal PC if that database is a centralized one. 

Cloud Database

Cloud Database

Cloud-based database apps perform in the cloud. Such apps are a great innovation as they come with a large amount of space to house data. Cloud is the technology over the internet that functions as a centralized database as they are always available, and one can access it from anywhere.

NoSQL Database

NoSQL Database

The only type of database that works uniquely from all the other application databases is NoSQL. General mobile app databases store data in rows and columns pattern, but NoSQL arrives with a flexible schema that permits a developer to house data in various shapes and sizes.

Commercial Database

Commercial Database

As organizations run on enterprise-based database apps, they need an extensive database to house employee information.

Here arrive commercial app databases. These provide login controls and ample storage to ensure data security. 

End-User Database

End-User Database

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 that we accept while browsing websites, the databases store cookies that help personalize your online experience. 

The whole process takes place in the background and doesn’t disturb any user information. 

Relational Database

Relational Database

The growing firms always try creating 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. 

Convert Your App Idea Into Reality

Let’s Build A New App Together

What Are The Best Databases For Mobile Apps?

Let’s now check out some top databases that are popular in developing Android apps and iPhone apps. You can choose the best one for your apps based on their needs. 

ArangoDB

ArangoDB

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

CouchDB

CouchDB

An open-source document-oriented database, Apache CouchDB uses various formats and protocols to transfer, store, and process its data. 

Written in: C, JavaScript, C++,

Firebase

Firebase

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. 

RethinkDB

RethinkDB

An open-source and 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++

SQLite

SQLite

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

Realm

Realm

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.

MariaDB

MariaDB

A commercially supported fork of the MySQL relational DBMS, MariaDB, is intended to stay open-source and free software. 

Written in: C, C++, Perl

MongoDB

MongoDB

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

Amazon DynamoDB

Amazon DynamoDB

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. 

PostgreSQL

PostgreSQL

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

Couchbase

Couchbase

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

Riak DB

Riak DB

A distributed NoSQL key-value data store, the Riak DB, provides high availability, operational simplicity, fault tolerance, and scalability. 

Written in: Erlang

InfluxDB

InfluxDB

An open-source time-series database, InfluxDB stores and retrieves time series data in fields. 

Written in: Go

Cassandra

Cassandra

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

Memcached

Memcached

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

Redis

Redis

An in-memory data structure store, Redis is used as an in-memory, distributed, cache, key-value database, and message broker. 

Written in: C

MySQL

MySQL

An open-source relational DBMS, MySQL is a fully managed database service used to deploy cloud-native apps. 

Written in: C, C++

SAP Adaptive Server

SAP Adaptive Server

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++

Solr

Solr

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

IBM Db2

IBM Db2

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

FileMaker

FileMaker

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. 

HBase

HBase

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

SAP HANA

SAP HANA

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++

Oracle

Oracle

A multi-model DBMS, Oracle is best for online transaction processing, mixed database workloads, and data warehousing. 

Written in: Assembly language, C, C++

Splunk

Splunk

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. 

Microsoft Access

Microsoft Access

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. 

Elasticsearch

Elasticsearch

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

Teradata

Teradata

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. 

Microsoft Azure SQL

Microsoft Azure SQL

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. 

Hive

Hive

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

Microsoft SQL Server

Microsoft SQL Server

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++

OrientDB

OrientDB

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

Neo4j

Neo4j

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

ORMLite

ORMLite

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

Firebirdsql

Firebirdsql

An open-source SQL relational DBMS, Firebirdsql runs on Microsoft Windows, Linux, macOS, and many Unix platforms. 

Written in: C++

Berkeley DB

Berkeley DB

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

What is the general criteria to choose the right databases for mobile apps?

Various criteria assist in picking a suitable database for your mobile apps.

Read on!

Structure of Your Data

Structure of Your Data

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. 

Size of Your Data

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. 

Data Modeling

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. 

Speed & Scale

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. 

Data Security

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. 

Mobile App Platforms Choice

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. 

Selection Criteria Based On Use Cases

Now, let’s check out the selection criteria as per the use cases:

Mobile Apps With Various Data Layers

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. 

Data Synchronization Between Backend Server And Local Database

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. 

For Highly Scalable Mobile Apps

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. 

Resolve Data Conflicts Between Devices

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.

Users With A Low Network Issue

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. 

Pushing Database Changes & New App Updates

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. 

You Have A Vision

We Have The Means To Get You There

What Are The Best Practices To Work With mobile App Databases?

Let’s now check out the best practices to consider for working with mobile app databases. 

Consider Databases That Follow Multiversion Concurrency Control (MVCC) Method.

Such a method permits simultaneous access with no interference in processes or threads. 

MVCC facilitates a reader to check data’s snapshot before the writers make changes by permitting read and write operations parallelly. 

Database MVCC
FirebirdYes
MongoDBYes
RealmYes
MySQLPartially, when used with XtraDB
MariaDBPartially, when used with XtraDB
RethinkDBYes
InformixDBYes
PostgreSQLYes, but inefficient
MemBaseYes

Predictive Caching

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. 

Database Caching To bring down the load

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 Challenges 

Low latency is vital for online gaming and real-time apps. High latency brings a wrong impression to the app users. Anything that moves down from 500ms is the high latency. 

So, you can follow any method to reduce the replication and latency of the database. Moreover, you can choose databases with, on an average lower latency:

  • PostgreSQL – for transactional operations in real-time.
  • Pipeline DB – SQL database best for streaming apps.
  • RethinkDB –  best for real-time apps.
  • MongoDB

Conclusion

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 criteria mentioned above. 

We hope this post gives you what you expect relevant to mobile app databases and finding a flexible mobile app database. 

If you want to create a mobile app, hire the best app development company that has skilled iOS and Android app developers who can turn your app ideas into reality.

Author

I am an eCommerce consultant, a member of the Forbes technology council with a decade of experience in the ecommerce development segment. My expertise can make your business overcome any obstacles while you are dealing with the Magento ecommerce platform!