Choosing Best Database for Your Mobile App: Important Features

Picking a database for your mobile app, you can unveil up the core of SQL, NoSQL and NewSQL mobile app databases types, their features and differences, in our previous article.

However, proceeding with the databases’ sphere, read on about NoSQL and NewSQL databases’ types to make your mobile app progress, and benefit from a few special tips on choosing an SQL or NoSQL database for your mobile application.

Opening the line, rip a few benefits of choosing the right database for your app.

Advantages of Choosing Perfect-Match Database for Your App:

  • Enhancing your user experience and customer satisfaction.

  • Maintaining your app’s strong working capacity and trouble-free operation with the suitable characteristics

  • Saving time with a database that’s “easy to forget about” with the scaling adaptability and possibility to adjust it to your business needs in the long run

Four types of NoSQL Databases

  1. 1

    Key-value stores - this is the simplest NoSQL type containing simple key-value pairs data, in case you need quick information retrieval connected with a key.

    Amazon DynamoDB and Redis databases are great examples of NoSQL stores whose simple structure makes them highly expandable, where the number of values is not defined, and there are no links between construction schemes and the values.

  2. 2

    Document stores - these databases save data in one JSON, BSON, or XML file, with all the same type of documents stored in collections (lists) in a tree/forest-type of documents allowing for quick key search but complicating the processing of elements with numerous linkages.

    Yet, document store databases facilitate creating an app, take, for rapid search of music singles. MongoDB and Couchbase stand as brilliant document store samples utilizing these bases for prompt prototyping, data analysis, and content management.

  3. 3

    Column stores quickly restore columns of data, saving them as a logical collection of values and can be easily reproduced, with their distinctive feature as containing both structured and unstructured data which is good for analytical operations but struggling with transactions (take as examples Apache Cassandra and Scylla database types).

  4. 4

    Graph stores consist of entities called nodes which are documents with free-form data, linked by edges defining their relationships. This type is beneficial for defining rapports between data points, i.e., searching for nodes with the most linkages and all the nodes linked. As the name implies, this type is utilized for exploring graph data structures (social networks and Web 3.0). Clear graph store cases are Datastax Enterprise and Neo4J.


NewSQL Databases

The solid competitor to SQL and NoSQL databases is a NewSQL software system, containing the attributes of both, but belonging to a relational database class. It addresses common SQL online transaction management issues such as adaptability, scalability, and composition without a database server, being fluently solved by NoSQL database attributes, at the same time conforming to ACID requirements and being able to expand without influencing the app logic or breaking the transaction model.

All these features provide a NewSQL database with high demand in future. with ClustrixDB, CockroachDB, NuoDB, MemSQL, VoltDB provided as the brightest examples. However, as of now, adoption of the NewSQL system is relatively restricted due to the absence of a complete SQL toolkit.

Choosing Best Database for Your Mobile App: Important Features

  • Type of data

    SQL systems - ideal for storing and managing structured data, noSQL databases support un- or semistructured data. Otherwise, opt for mixing the systems.

  • Data safety

    ACID-conformant relational databases are at the top of the security in trading operations.

  • Scalability

    Scaling the app coverage vertically or horizontally: noSQL systems with key-value attributes scale data horizontally, and SQL - pose data in vertical rows.

  • Analytics performance

    With the need for placing large structured data amounts for the analysis, consider data warehouse, while for unstructured data, you should pick data lake.

  • Integration possibility

    For example, ArangoDB is perfect in productivity, but poor in tool support. Therefore, it won’t be stable in managing complex projects.

Index of the Best Database Management Systems for Your App in 2022


The first-to-choose MVP type giving you the chance to test your sIs the DBMS behind Airbnb, Netflix, Tesla, Uber, LinkedIn, Facebook, Twitter & YouTube. MySQL drawbacks: if you need more sophisticated support, it demands supplementary budget, also for incremental backup and modifying the data structure, which doesn’t happen in other systems. This base is written in: C, C++.


Is an object-source relational database where the data is put in the form of objects, not rows and columns. It’s the best system for huge datasets (terabytes of data) with the foremost security due to the roles’ strict succession. PostgreSQL bonus - all the support and docs are free and provided by the volunteer community.

Amazon DynamoDB

Is a hosted NoSQL database maintained by Amazon Web Services, with stable performance and scalability, protected user expertise, and a compact and a simple API allowing for simple key-value access and extended queries.


Is a multi-model database, optimal for online transaction management, mixed database workloads, and data warehousing. This database is based upon Assembly language, C, C++.


Is an open-source column-oriented database producing analytical data reports. ClickHouse offers bonuses such as high productivity, fault resilience, data extensibility, and saving big data amounts while compressing it. Good thing is that similar to SQL language is supported in this software system standing behind Spotify, Uber, and Deutsche Bank apps.


Is the best data system for web apps, but not optimal for mobile. As a non-relational system, it stores the data in BSON documents to be readily transmitted between web apps and servers in a handy way. MongoDB drawbacks: it saves key names for each value burdening the app memory, allows nesting for no more than 100 levels.


Open-source document-based system indexing any kind of stats (text, geospatial, or numerical) in JSON format; enabling smooth search and extraction of data. Bonus - swift horizontal scalability. Elasticsearch 6.7 version allows for managing and storing data life cycle in hot, cold, or warm nodes, with hottest nodes found in a quicker mode, due to using state drives (SSDs), the top-notch storage device type.


Is an open-source key-value data bank utilized as a caching layer for dealing with another data bank. It is very fast and smooth in data setting and configuring. Redis drawbacks: stores only sets, lists, sorted sets, strings and hashes with no encryption, with the main goal of conserving basic data sets.

SQL or NoSQL Database: What’s Better?

Make a note: you can mix databases for one project, but again, only after a good analysis of your app technology stack and the project cost evaluation. Be careful to combine databases as, for instance, Redis can be effectively used in merge with PostgreSQL (for token storage and cache).

Herewith, MongoDB and PostgreSQL complement each other in terms of using resources and storing information (about posts, profiles, likes, and followers), providing excessive functionality.

For instance, having weighed all your pros and cons, choose a concierge or a crowdfunding campaign MVP to cover the predefined TA audience with the good product and take your time to wait for the positive customer response. Considering the MVP type to choose, remember that everything depends on the primary functionality to be highlighted in your MVP solution. Herewith, the final-end goal of your MVP is effectively developing a perfect solution assuaging the user’s pain. So, never give your valuable idea up and stick to the words of glorious sir Winston Churchill,”Success consists of going from failure without loss of enthusiasm.”

Another important thing to refer to are the database CAP aspects, which are consistency, availability, and partition tolerance. This acronym implies that it’s impossible to have all the database aspects at the perfect level in a single database software, forcing a SEO to choose only two features.

So, picking two out of three best features for your application data, regard thoughtfully your project priorities and needs of storing and managing the application data.


However, a NoSQL database would be a great selection for your project if it needs to be developed with the agile technology and swift implementation criteria. Take MongoDB which is swifter than MySQL in managing broad unstructured amounts of data. On the other hand, with the need of potential scaling, you would better choose a MySQL database.


Drawing the line under the article, in choosing your perfect database, consider the minimum demands for your system: your data size, data type, scalability, analytics performance, and integration with other tools in your software system. Targeting a serious app architecture and the long-term project deployment, consider focusing on a compound NoSQL bundle or a MongoDB database demanding a lot of support, with a competent developer team to help you realize your project with high-end quality .

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