Your IT project would involve creating a mobile application or software. Choosing the right database is crucial. Whether you are creating a new mobile application or adding additional features, selecting the correct database might be difficult. Your current database is inadequate to support millions of users and regular updates.


You will need a custom software development company to help you find a suitable database management system (DBMS). The DBMS ensures an interface between your application and the underlying database. It ensures that the correct data is accessible when required for the chosen user group.

When deciding between a SQL database and a NoSQL database for your applications, you must consider the specific requirements of your applications.

When starting with the database for software, the following factors will assist you in selecting the optimal database for your projects.

Key questions: What are the most important questions to ask?

When choosing the database management system for your technology's functions, consider if the database you're now using can meet all your needs.

To begin with, you can ask the following questions

  • If your app becomes viral, what will you need from your database to support it?
  • When scaling up your app or software, can you add additional features to your database?
  • Is your choice of the database based exclusively on what you need to display your demo by getting the right database management service?

You may be tempted to start MongoDB and be done with it. Also, you have a choice of SQL vs NoSQL; remember that making a hasty choice now might lead to regret in the future.

What are the benefits of DBMS, and why should you consider it for your project?

  • Using database management software tools ensures consistent performance for users.
  • There is less chance of mistakes, particularly regarding user data.
  • Allows firms to save money on data management expenditures by simplifying the data administration process.
  • Data may be accessed more quickly at a certain moment.
  • Provides the highest protection possible, avoiding data loss and theft.

Types of Database to consider

Before choosing a DBMS, you should consider the following factors. You may save time and frustration using a database management system (DMBS), whether using PostgreSQL, MySQL, or NoSQL.


When choosing a database management system for your company, there are several aspects to consider. Your current database, business goals and scalability requirements should all be considered when choosing a new one.

Here are some of the key types of databases that you need to choose from for your product development.

NoSQL and SQL Databases

Choosing between a SQL (relational) and a NoSQL (non-relational) data structure is the most important consideration when choosing the database for product development.

It is important to remember that although both databases are feasible solutions, they have important distinctions.

NoSQL DBs do not have a standard organized schema for all entries, unlike relational databases, which include rows and columns. Different entries in a JSON-based NoSQL database have a variety of fields.

RELATIONAL Database Management System (RDBMS)Non-relational or distributed database system
A database having static/fixed/predefined schemaDatabase with dynamic schema
Is not ideal for hierarchical data storageThe best option for hierarchical data storage
Suitable for executing sophisticated queriesNot the best option for running complex queries
Vertically Scalable databaseHorizontally scalable database
Goes with Atomicity, Consistency, Isolation, and Durability (ACID)Follows Consistency, Availability, Partition Tolerance(CAP)
Examples: PostgreSQL, Oracle, MySQL, Oracle, MS-SQL Server etc.Examples: Neo4j, GraphQL, HBase, MongoDB, Cassandra, etc.

Read More: MongoDB Vs MySQL: Which database is best for your business

Columnar DBs

This DB's atomic unit is a table column which implies that data is kept in numerous columns. It makes column-based searches faster, and since the data on each column is relatively consistent, it ensures data compression.

Key-value DBS

Key-value DBS queries are one of the single queries that can be made. For instance, a query like “select all records where city = Philadelphia” might not be supported since it crosses several record values.

When using this database, use the TTL field (time to live), allowing you to choose when a particular entry in the database should be removed.

Document-oriented DBS

Documents are JSON files, and each document's schema may differ.

The indexing of certain fields in a document enables quicker queries based on those fields in a document database (DB). This way, it forces all the documents to have the field.

Graph DBs

Graph DBs have nodes that stand for entities and edges that show how different records in the database are connected.

Factors to consider when choosing the right database

The DBMS is responsible for how your applications and the database work together. It makes sure that the right data is available when the user group asking for it needs it.


Before choosing the database management system for your IT project, you should consider a few key aspects.

Data consistency

Getting the necessary information should not be a big deal. However, the need to maintain consistent data increases when additional sources are added to the database. Therefore, the ability to set consistency rules should be considered when choosing a new database management system (DBMS).

Consistency refers to how database transactions are constrained only to modify the data directly impacted by them, according to predetermined constraints. SQL databases have a reputation for being more reliable than NoSQL databases when it comes to data consistency.

This implies that the former is preferable if your application necessitates reading the most recent data.

Data protection & security

Access protection and encryption for personal data are necessary. Here, encryption mechanisms provided by each DBMS vary depending on how procedures and access privileges may be set up.

When evaluating a database management system and data security method, it is necessary to consider the database structure when deciding on a data security method.

Always investigate the database's safety mechanisms in case of a system breakdown or failure. There are additional security concerns when synchronization and decentralized storage are used.

Also, it is necessary to address concerns like data in motion, data at rest, reading and writing of data, etc. You can also incorporate customized or standard authentication.

To sum up, a database should have the best safeguards to guard against the loss of confidentiality, integrity, and accessibility of data.

Resolve data conflicts

You may encounter data conflicts when a user on one device changes data that another user on a separate device has already made. Data can turn inconsistent across different versions within the same database.

As a result, resolving these issues requires choosing the best database system for product development.

The conflict resolution database system must be adaptable to resolve conflicts across users, cloud systems, devices, and third-party integrations.

Data shape

Strongly typed data is often stored in rectangular tables with rows and columns in SQL databases. Indexes speed up certain searches, while JOINS lets you query many tables simultaneously.

These techniques are based on the well-defined relationships between the database tables. If needed, weakly-typed JSON, including arrays and nested documents, are often stored in document databases.

Nodes, edges, triples, and quads are stored in a graph database. Key-value and columnar NoSQL databases are also available.

In some cases, you may fetch data in a form that can be used for analysis; in others, a transformation (to other forms) becomes necessary.

A database may be created on top of another database. Key-value stores, for example, may be used to support practically any database.

Considering service and implementation costs

When choosing database management as part of the implementation and Total Cost of Ownership (TCO), examining the modifiability and availability of support and documentation is important.

It is necessary to constantly consider your business’ specific database management system requirements throughout development. Choosing the right set of tools for a database gets easier if you precisely understand your requirements and cost-effectiveness.

Data modeling for multiple databases

Doing data modeling before settling on a database is a good idea. Leverage this model to see how the database will be structured and how it meets your business needs.

Data modeling is necessary if your app includes useful functions like reporting, search, or location-based functionality. Multiple databases are necessary to handle these programs' various sorts of data.

Here, consider several databases like Uber that leverage MySQL, MongoDB, and others. Their CDN (Content Delivery Network) is powered by MongoDB, while MySQL powers their business logic. They could store a lot of data quickly and easily because of MongoDB.

Multi-platform support

If you are into creating an application, think of its platform — iOS or Android? Also, if you want to add support for more platforms in the future, you must do it right now.

Many applications these days include a web companion app or native desktop software. Therefore, if you want a database for your business, consider if it supports multiple platforms.

For instance, React Native is a great option if you're developing mobile applications for iOS and Android. Developing for Android and iOS simultaneously is simply because of the ability to exchange code across the two platforms. Besides that, database compatibility is also necessary.

Stability and maturity

First, you need to know whether your Database Administration (DBA) staff is well-versed in using newer technologies. If feasible, you can consider self-hosting a database. It can be intriguing if your organization has never used it before, but it is not a good idea if you don't have any expertise with the database.

Setting up a database is demanding. Especially when dealing with large datasets, you need to run the setup, ensure configuration, and provide fine-tuning.

When it comes to long-term production reliability, sometimes the "old" organization's self-hosted work-horse is the best option.

Legal considerations

There are several laws in place to protect the personal information of customers who trust your software and applications.

Data privacy, protection, and placement come under the purview of GDPR in the European Union.

Regarding healthcare, HIPAA and GLBA govern how financial companies handle consumers' data in the US. The new California Consumer Privacy Act (CCPA) protects consumers and promotes privacy rights.

You can handle the data within the legal boundaries if you ensure following any or all of these rules as a part of best practices while choosing a database. Often, some of the databases may have security or privacy flaws that may have negative consequences as it is difficult to identify flaws manually in such databases.


While you may consider all or some of the factors mentioned above when selecting a database for product development, it will be affected by the change in software and mobile application environment.

This is possible either during the feature upgrade or by adding a new feature addition. Your business will ultimately benefit when you consider the points mentioned earlier. Here, you need to choose the DBMS that can accommodate a wide range of queries is critical here.

These factors can also help you create your list of needs and evaluate the available DBMS in the market. For relational DBMS, the most prominent vendors are Oracle, IBM DB2, MSSQL, AWS Web Services, and MongoDB for NoSQL.

After deciding on the database and rolling out the product, ensure implementing a strategy to monitor and keep up the DBMS operations at peak performance. Also, consider future needs and scalability when selecting a database.



The success of your application largely depends on the right database you may pick.

It is better to analyze the underlying purpose and needs of the data store. A lot of your application’s success depends on your app's ability to meet the user demands while also using the data it collects.

First, an ideal database model will have no duplication (redundant data). Second, it should ensure the accuracy and completeness of data. A perfect database model will discard anything that is not useful and help leverage its predictive and explanatory ability.

Most database management systems are developed with a certain data model in mind and require its users to adopt that model, but some do support alternative models of database management system.

Database models help understand the way data is linked, stored, accessed and updated in the DBMS. It uses a set of symbols and language to represent the information so that your business can communicate and comprehend it.

Major types of database models in DBMS includes

  • Associative Data Model
  • Context Data Model
  • Entity-Relationship Model
  • Flat Data Model
  • Object-Oriented Data Model
  • Object-Relational Data Model
  • Relational Model
  • Semi-Structured Data Model

Organizations looking to implement "big data" databases can process and store a wide range of information quickly and efficiently. It uses unstructured and semi-structured datasets need that are transformed into different formats in a way for analytics tools to use it.

makes NoSQL databases like MongoDB an excellent alternative for storing massive amounts of data.

Businesses looking for big data implementation can consider the following database

  • MangoDB
  • HBase
  • Cassandra
  • Neo4j
  • CouchDB
  • Terrstore
  • Riak
  • FlockDB, etc.

Krutika Khakhkhar

Krutika is an accomplished software project manager with years of experience leading complex software development projects from conception to delivery. They possess a unique combination of technical and project management skills, which enables them to successfully manage and motivate cross-functional teams to deliver high-quality software solutions.

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