A Practical Guide in Choosing the Best Database for Your Application

It is crucial to choose the right database for your application. With the abundant number of options that are available to choose from, it could be hard to know which database is best for the needs and requirements for your application. A database is the backbone of most existing applications. It is used to store, retrieve and manage data as efficiently as possible. It is very important to choose the right database when building an application, as it can significantly impact the performance and reliability of the application.

This practical guide was made with the aim to help you navigate through the process of choosing the best suitable database for your application.

Understanding Your Application’s Needs

Every application requires different needs; therefore you need to fully understand what the specific needs are for your application. The following factors are:

1. Data Structure

The data structure is about how information is organised and stored. Some applications require a well-defined schema with relationships between tables, which is where a relational database excels. For instance, if your application deals with customer orders, inventory, and supplier information, the structured format of a relational database can enforce data integrity and enable complex queries.

On the other hand, if your application handles diverse data types or the structure of the data is expected to change frequently, a non-relational database might be more appropriate. These databases are more flexible in terms of the data models they can accommodate, whether it’s key-value pairs, wide-column stores, documents, or graphs.

1. Volume of Data

The volume of data your application will generate and store is a critical aspect. Small to medium-sized datasets might be easily managed by most databases, but as data grows into terabytes or petabytes, you’ll need a database designed for high volumes of data. This is where databases with strong horizontal scaling capabilities come into play, as they can distribute data across multiple servers to manage large datasets efficiently.

1. Scalability

Scalability is about the database’s ability to handle growth. There are two types of scalability to consider:

• Vertical scalability:

This involves adding more resources (CPU, RAM, storage) to your existing server. Relational databases traditionally handle vertical scaling well, but it can become expensive and has physical limits.

• Horizontal scalability:

This involves adding more servers to your database infrastructure to distribute the load and data. NoSQL databases are typically designed for easy horizontal scaling, allowing them to handle massive amounts of data and high user loads with ease.

1. Security

Security encompasses the measures and features that protect your data from unauthorised access and breaches. It includes aspects such as:

• Data encryption: Protecting data at rest and in transit from eavesdropping or tampering.
• Access control: Defining who can access what data and what they can do with it.
• Auditing: Keeping logs of data access and changes to ensure traceability and compliance with regulations.
• Compliance: Adhering to legal and industry standards like GDPR, HIPAA, or PCI DSS.

Understand Your Data Model

The first step in choosing the right database is to understand your data model. Different databases are designed to handle various types of data structures.

1. Relational Databases:

Relational databases, such as MySQL and PostgreSQL, excel in managing structured data with well-defined relationships. They are suitable for applications with complex queries and transactions, ensuring data integrity through ACID compliance.

These databases are structured and use a predefined schema. They are ideal for applications that require complex queries and transactions, such as financial or inventory systems. Popular examples include MySQL, PostgreSQL, and Microsoft SQL Server.

1. NoSQL Databases:

NoSQL databases like MongoDB and Cassandra are ideal for unstructured or semi-structured data. These databases are well-suited for applications with high write loads, scalability requirements, and flexibility in handling diverse data formats.

NoSQL databases are more flexible and can handle unstructured data. They are suitable for applications with rapidly evolving data models or those that require horizontal scaling. Examples include MongoDB (document store), Cassandra (wide-column store), Neo4j (graph database), and Redis (key-value store).

A Closer Look of SQL Databases

SQL databases have been the industry standard for decades. They use Structured Query Language (SQL) for defining and manipulating data. SQL databases are ACID-compliant (Atomicity, Consistency, Isolation, Durability), ensuring reliable transaction processing.

Advantages:

• Structured Data: They excel at handling structured data with relationships between different entities.
• Complex Queries: SQL databases support complex queries and reporting.
• Maturity: There is a wealth of knowledge, tools, and best practices available.
• Transaction Support: They provide robust transaction support, which is critical for applications requiring data integrity.

Considerations:

• Scaling: SQL databases traditionally scale vertically, which can become a bottleneck.
• Schema Changes: Modifying the schema can be challenging and may require downtime.

A Closer Look of NoSQL Databases

NoSQL databases emerged to address the limitations of SQL databases, particularly in terms of scalability and flexibility.

Advantages:

• Schema-less : NoSQL databases allow you to store unstructured data without a predefined schema.
• Horizontal Scaling: They are designed to scale out across multiple nodes easily.
• Specialised Data Models: Different NoSQL databases are optimised for specific data models and access patterns.

Considerations:

• Consistency: Some NoSQL databases trade strong consistency for availability and partition tolerance (CAP theorem).
• Maturity: While they have matured significantly, NoSQL databases may not have the same level of tooling and community support as SQL databases.

Analysing Popular Database Options

Let’s take a closer look at some popular databases:

• MySQL: An open-source relational database known for its reliability and ease of use. It’s a good fit for web applications and can handle a moderate amount of data.
• PostgreSQL: Another open-source relational database that is known for its advanced features, such as support for JSON data types and geospatial data. It’s well-suited for applications that require complex data processing.
• Microsoft SQL Server: A commercial relational database with a comprehensive set of features for enterprise applications. It offers strong security features and powerful analytics capabilities.
• MongoDB: A document store that stores data in JSON-like documents. It’s ideal for applications with evolving data models and benefits from its expressive query language.
• Cassandra: A wide-column store designed for high availability and scalability. It’s a good choice for applications that require fast reads and writes across large amounts of data.
• Neo4j: A graph database that excels at handling data with complex relationships and interconnected elements. It’s perfect for social networks, recommendation systems, and fraud detection.
• Redis: An in-memory key-value store used for caching and real-time analytics. It’s incredibly fast and is often used to boost the performance of applications.

Performance and Scalability

The key in choosing a database relies on performance. Complex transactions are better suitable for SQL databases, while NoSQL databases are better for read-heavy operations or for dealing with large volumes of data. Consider the read/write ratio of your application and whether it requires more complex transactions or simple, fast data access.

Another important factor is scalability. If you have expectations for a rapid growth, a database that is able to scale horizontally, NoSQL databases might be more suitable. However, if the difficulty and complexity of your data is quite high, it might be better to use the vertical scaling that SQL databases offer.

Security and Compliance

Security features such as encryption, access controls, and auditing are essential. Compliance with industry standards and regulations, such as GDPR or HIPAA, may also influence your choice. Commercial databases often come with built-in security features, while open-source options may require additional configuration or third-party tools.

Cost Considerations

Cost is a significant factor for many organisations. Open-source databases like MySQL and PostgreSQL offer robust features without licensing fees, but you may incur costs for support and maintenance. Commercial databases like Microsoft SQL Server come with licensing fees but offer comprehensive support and advanced features.

Community and Support

A strong community and support are invaluable. Look for databases with active communities, extensive documentation, and professional support options. This can be particularly important for troubleshooting, performance tuning, and staying updated with the latest best practices.

Below are graphics that could help you in deciding what database is best suited for your applications,

When you select a relational database, you should take into account your data amount and database scalability, then decide based on the presence of a cold backup system in the database, choosing whether or not to use the TokuDB storage engine, and if you want to utilise a proxy.

While choosing a NoSQL database, it’s critical to consider numerous factors to choose the best method, such as whether to use a master-slave architecture, client-side sharding, a distributed cluster system, or particular NoSQL solutions like Couchbase or HiKV.

References

Jarke, M., & Vassiliou, Y. (1985). A framework for choosing a database query language. ACM Computing Surveys (CSUR), 17(3), 313-340.

June2020. (n.d.). App Builder User’s Guide. Oracle Help Center. https://docs.oracle.com/en/database/oracle/application-express/20.1/htmdb/creating-database-applications.html

Leitao, G. (2021, March 19). How to efficiently choose the right database for your applications. dzone.com. https://dzone.com/articles/how-to-efficiently-choose-the-right-database-for-y

Lerner, R. M. (2007). Open-source databases, Part III: choosing a database. Linux Journal, 2007(158), 17.

Lourenço, J. R., Cabral, B., Carreiro, P., Vieira, M., & Bernardino, J. (2015). Choosing the right NoSQL database for the job: a quality attribute evaluation. Journal of Big Data, 2(1), 1-26.

PingCAP. (2023, December 15). Choosing the right database for your applications | PingCAP. https://www.pingcap.com/case-study/choosing-right-database-for-your-applications/

Shaikh, Z. (2023, April 11). Choosing the right Database: A guide for developers. Medium. https://proteinshaikh.medium.com/choosing-the-right-database-a-guide-for-developers-3638e75ab7f2

Tremblay, T. (2023, December 20). 4 Examples of database application. Kohezion. https://www.kohezion.com/blog/4-examples-database-application

Tatum, M. (2023, December 18). What is a database application? Easy Tech Junkie. https://www.easytechjunkie.com/what-is-a-database-application.htm