A database enables quick, secure, and effective maintenance, updating, and editing of data that has been stored. The ability to store enormous volumes of data from a network of IoT devices, track your company’s inventory systems, and create web applications are just a few examples of the many real-world situations where a database can be valuable.
There are various current database types available, each with their own set of benefits and drawbacks. If your system need a relational database system, you should generally go with MySQL, PostgreSQL or Microsoft SQL. And, if your need point towards a Non-relational database system, options may vary between MongoDB, Apache Cassandra, Redis and Firebase.
In this article, we briefly describe the most common current database type, and point you towards which one is best for your system.
So, Which Database Is The Right Choice ? This question is frequently made by programmers and students when deciding on a database for a project. Working with a database you are already familiar with is great if performance is not a top priority for your system, but think about a scenario where your application grows and encounters problems after a few years. Fixing the problem will become a nightmare for developers and administrators. No matter if you are starting from scratch or working on an established project, it is crucial to understand the database’s limitations and recognize when to incorporate another form of DB into your work.
STEP 1: Choose a Database Management System
Relational Database Management Systems (SQL)
RDBMSs (relational database management systems) employ SQL, a database management language that provides a highly structured and organized method of information management. Relational databases utilize rigorous, categorical parameters that make it simple for database users to organize, retrieve, and manage information within those parameters, much like a phone book includes multiple categories of data (name, number, location, etc.) for each line of data.
Non-Relational Database Systems (Non SQL)
Information can be organized more loosely in non-relational databases; it’s like putting it in various file folders. This is crucial for the storage of unstructured data and for exposing it to robust business intelligence systems for AI-based analysis. Additionally, you can store unstructured data in this database type that you intend to arrange later.
Non-relational databases are also a perfect choice for web-based applications that enable websites to update live without requiring a page refresh.
STEP 2: Choose an appropriate database
Owned and run by Oracle, MySQL is a free, open-source RDBMS solution. Although MySQL is freeware, it receives regular security and feature updates. Large businesses can upgrade to premium MySQL versions to have access to more features and user support. Despite not previously supporting NoSQL, MySQL now does it as of Version 8 in order to compete with competing products like PostgreSQL.
For companies who require a solution with enterprise-level features but are working on a tight budget, MySQL is a particularly important RDBMS option. It is a cutting-edge RDBMS with a free tier that is incredibly strong and dependable.
An open-source, cost-free database engine with limitless growth options is PostgreSQL. Both relational nor non-relational data formats are compatible with PostgreSQL.
PostgreSQL has a loyal user base and has won the coveted Database of the Year Award twice as a highly regarded DBMS that has been in use since the early 1990s.
PostgreSQL’s history of working with both structured (SQL) and unstructured (NoSQL) data is an intriguing trait.
This is a great option for businesses of any size because PostgreSQL is totally free and scalable. More crucially, PostgreSQL is suited you if you can gain from a DBMS with built-in JSON support.
Redis is an in-memory data structure store that is open source, used as a database, cache, message broker, and streaming engine. Redis has a variety of data types, including bitmaps, hyperloglogs, geographic indexes, streams, lists, sets, and sorted sets with range queries. Redis offers various levels of on-disk persistence, transactions, built-in replication, Lua scripting, LRU eviction, high availability with Redis Sentinel, and automatic partitioning via Redis Cluster.
However, Redis does not fit as a Database if we need to store very large data sets, or expect our data to grow very fast.
Designed specifically for applications that handle unstructured data, MongoDB is a free, open-source database engine. Even while add-ons now make it possible for them to manage non-relational data, most DBMSs were designed for structured data, which is why MongoDB succeeds where other DBMSs fall short. Structured data can also be used with MongoDB, but performance lags are expected because relational data wasn’t the database engine’s original focus.
MongoDB can be the best option for you if you’re building an application on top of an operational database and you require an extremely quick response time. However, you might want to choose a different platform if you’re creating a data warehouse for analytics.
Other database systems, can represent a good alternative for the list above. We recommend the following:
- Microsoft SQL
- Google Firebase
- Appache Casandra