Open In App
Related Articles

Top 7 Databases to Learn in 2023

Like Article
Save Article
Report issue

A database is just like a room in an office where all the files and important information can be stored related to a project. Every company needs a database to store and organize the information. The information that we store can be very sensitive, so we always have to be careful while accessing or manipulating the information in the database. 


For building different kinds of applications such as Web, Enterprise, Embedded Systems, Real-Time Systems, AI, ML, HPC, Blockchain, IoT, etc you may have to choose one or more databases. Over the years programmers and industry specialists have shown their love for databases that fulfilled their requirements.

Choosing the right database is also dependent on the purpose of the project. Around 20-25 years ago choosing a database for an application wasn’t a challenging task. Most of the time developers preferred relational databases to configure their applications. But today it has become a challenging task due to the advancement in applications. 

Modern software development (applications built on the Microservices, Cloud, Distributed applications, Global Scaling, Semi-Structured Data, Big Data, Fast Data, and Low Latency Data) requires traditional databases joined with various NoSQL, NewSQL, and Cloud databases. 

Today more than 343 databases are out there in the tech world which is a very huge number. To choose the right database you need to be familiar with the pros and cons of some popular databases. If your goal is to become a software or technical architect (of course they are the ones who make the decisions to choose the right technology) then it’s good to gain knowledge about these databases as much as you can. 

In this blog, let’s discuss some critical databases which you should learn or get familiar with in 2023. Before that let’s have a quick look at the ranking of the most popular databases According to DB Engines below is the list…

image source: DB engines

If we take a look at the previous year’s survey then below is the data available on StackOverflow

Image source: Stack Overflow

1. Oracle

Oracle was created by software engineer Larry Ellison (current CTO of Oracle Corporation) in 1979. Oracle is the leading commercial RDBMS system written in assembly languages C, C++, and Java. 21c is the latest version of this database which has many innovative features.

Oracle sits on the top of the databases. It is the most widely used RDBMS overall. It takes less space and quickly processes data and you can find some new good features like JSON from SQL as well. Some other features of this database are given below…

  • ACID transactional guarantee. If we talk about CAP then it offers immediate Consistency as a single Server.
  • It supports Structured Data (SQL), Semi-Structured Data(JSON, XML), Spatial Data, and RDF Store. Also, it offers various access patterns depending on the specific data model.
  • Supports both OLTP and OLAP workload.
  • Fulfills the requirement of high availability, performance, scalability, data warehousing, etc.
  • Oracle provides functionality for Cloud, Document Store, Key-value storage, Graph DBMS, PDF Storage, and BLOG.

2. MySQL

MySQL is the most popular and widely used database in the tech world, especially in web applications. It was introduced in 1995 by two software engineers Michael Widenius and David Axmark. This database mainly focuses on robustness, stability, and maturity. The most common use of this database is for the purpose of web applications.

MySQL uses a structured query language and it is written in C and C++. The latest version of this database is MySQL 8.0 which has a better recovery option. For different editions, MySQL has different features. Some of the key features are given below…

  • MySQL is open-source with two licensing models: free Community Server and proprietary Enterprise Server.
  • It comes with the ACID transactional guarantee and in CAP theorem it offers immediate Consistency.
  • MySQL offers horizontal partitioning (sharding). If your software is built on this database then surely you will get high availability and high throughput with low latency.
  • MySQL supports most of the programming languages such as C, C++, Python, Java, PHP, and Tcl for client programming.
  • MySQL Cluster offers multi-master ACID transactions.
  • MySQL supports large databases, up to 50 million rows or more in a table.

3. Microsoft SQL Server

MS SQL server is the variant of Sybase SQL server. Developed by Microsoft this database was launched in 1989. MS SQL Server and Sybase SQL Server have many common features. MS SQL Server is written in C and C++. 

This database has excellent tooling support from Microsoft for both On-premise and Cloud. It is available on both Windows and Linux platforms. Like the other modern database, MS SQL is not as innovative or advanced but it has gone through major updates and overhauls over the years.

This database has many editions such as Azure SQL Database (cloud-based version), compact edition, enterprise edition (preferred by most companies), and developer edition. Some of its features are given below.

  • Platform independent with high performance.
  • ACID transactional guarantee. In CAP theorem it offers immediate consistency. 
  • Support for many server-side languages such as T-SQL, .NET languages, R, Python, and Java.
  • Support for Structured Data (SQL), Semi-Structured Data(JSON), and Spatial Data.
  • It can be integrated with non-relational sources like Hadoop
  • It uses row-level security, dynamic data masking, transparent data encryption, and robust auditing.
  • Comes with custom-built graphical integration that saves a lot of time for users.
  • It allows you to create various designs, and tables, and view data without syntax.

4. PostgreSQL 

This open-source database was introduced in 1996 by Michael Ralph Stonebraker. PostgreSQL originated from the Ingres database and Michael was the leader of the Ingres team. The database was originally named POSTGRES. Michael also got the Turing Award for his work in PostgreSQL.

PostgreSQL is written in C and it is used by companies who have to deal with a large volume of data. A lot of gaming apps, database automation tools, and domain registries use this database. Some of its features are given below…

  • ACID transactional guarantee. In the CAP theorem, it offers immediate consistency. 
  • Although it’s an Object-Relational DBMS users are free to create NoSQL databases. You can use this database with a transactional guarantee of an SQL database and horizontal scaling of the NoSQL database. You can use this database where distributed SQL is required.
  • More advanced indexes like partial Index, and Bloom Filters. It allows you to create a non-blocking index in PostgreSQL.
  • High scalability, predefined functions, easy data portability, and multiple interfaces.
  • Support for Structured Data (SQL), Semi-Structured Data (JSON, XML), Key-Value, and Spatial Data.
  • Comes with advanced reliability and disaster recovery feature.

5. MongoDB

When it comes to using a NoSQL database MongoDB is the top priority for enterprises. Using object-oriented programming languages it is difficult to load and access data into RDBMS. You will have to do additional application-level mapping. 

MongoDB resolves this issue, especially handling Document Data. MongoDB is a simple, object-oriented, dynamic, and scalable database. You don’t need to deal with columns and rows like the traditional databases. You store the data object as separate documents inside a collection. 

10gen software company released this database in 2009 and in the last decade, this database has gone through many improvements and innovations. It is written in C, C++, and JavaScript. You can use this database for mobile apps, real-time analytics, and IoT, and can provide a real-time view of all your data. Some of its features are given below.

  • Fast, easy to use, deployment flexibility, high performance, high availability, and easy scalability. Using Auto-Sharding you can easily do horizontal scaling. It offers built-in replication via primary-secondary nodes. 
  • It is CP (Consistent and Partition tolerant) in the CAP model.
  • ACID transactions (Distributed multi-document) with snapshot isolation.
  • Supports graph search, geo-search, Map-Reduce query, and text search.
  • MongoDB Inc. offers a full-text search engine (Atlas Search) and a data lake (Atlas Data Lake).
  • Queries can be easily optimized for output.

6. Redis

Redis (Remote Dictionary Server) was introduced by Italian developer Salvatore Sanfilippo. He created this database when he was working on his startup, and he faced scalability issues with traditional databases. He wanted to develop a real-time log analyzer. He created Redis as a distributed in-memory key-value store.

Sooner Redis got popularity and now it is used extensively in the industry. Some of its features are given below.

  • Used as a distributed, in-memory key-value database. Redis can also be used as a distributed cache and message broker with optional durability,
  • Supports a wide range of data structures such as strings, hashes, lists, sets, bitmaps, hyper logs, sorted sets with range queries, and geospatial indexes with radius queries.
  • In the CAP theorem, it supports CP (Consistent and Partition tolerant).
  • High scalability with built-in replication, automatic failover, and sharding via Redis Cluster. 
  • Good for real-time use cases, e.g., Inventory systems

7. IBM DB2

In 1983 IBM released its first commercial relational-database product, IBM DB2. Initially, it was released to mainframe machines but in 1987 IBM released DB2 LUW for Windows, Linux, and Unix systems as well. the latest release of DB2 is 11.5 which runs queries faster. 

The database supports a relational model but in recent years it has evolved a lot and not it has been extended to support object-relational features and non-relational structures like JSON and XML. Some of its features are given below…

  • Supports private as well as cloud environments.
  • ACID transactional guarantee.
  • Support for structured data (SQL), semi-structured data (JSON), and Graph Data.
  • It also works as a Master database. It provides great OLAP support via IBM BLU Acceleration.
  • It offers AI-dedicated capabilities that are designed to manage and structure complex data. 
  • Horizontal scalability is possible via Db2 pureScale.

Final Note

We have shown 7 databases to use in 2023.  Apart from these 7 databases other databases that are going to be used a lot in industries are Elasticsearch, Cassandra, MariaDB, and Firebase. 

MySQL and PostgreSQL are the leaders in the open-source and free database. If we talk about commercial databases Oracle is gaining popularity. In NoSQL databases, MongoDB, Redis, and Cassandra are the leaders. Depending on the project requirements industries are using it. Hope this was helpful to give you a high-level overview of the top databases for 2023.


1. What are the types of databases?

There are mainly five types of databases that are extensively used by developers as well as other communities.

  • Hierarchical databases
  • Network databases
  • Object-oriented databases
  • Relational databases
  • NoSQL databases

2. What are the advantages of Databases?

There are numerous advantages of Databases, a few of them are:

  • Data consistency
  • Improved data security
  • Faster data access
  • Scalability
  • Data backup and recovery

3. Where to learn DBMS?

There are several learning platforms that provide tutorials and courses for DBMS. To learn DBMS you can visit: DBMS Tutorial – Database Management System 

Last Updated : 20 Sep, 2023
Like Article
Save Article
Share your thoughts in the comments
Similar Reads