Best database for a chat application

When building a chat application, you typically need a database to store and manage the chat messages, user information, and other relevant data. Here are some common database options for chat applications.


Relational databases

Relational databases such as MySQL, PostgreSQL, and SQLite are widely used for chat applications. They provide structured storage and support for complex queries, making them suitable for handling large volumes of data and user interactions. Relational databases offer features like ACID (Atomicity, Consistency, Isolation, Durability) transactions, which ensure data integrity.

NoSQL databases

NoSQL databases like MongoDB, Cassandra, and Firebase Realtime Database are popular choices for chat applications. They offer flexibility in handling unstructured or semi-structured data and can scale horizontally to accommodate high read and write loads. NoSQL databases excel in scenarios that require fast, real-time updates and the ability to handle large amounts of data.

Message queues

Chat applications often utilize message queues like Apache Kafka or RabbitMQ for handling real-time messaging. Message queues provide reliable and scalable communication channels between different components of the chat application. They help in distributing messages, ensuring message ordering, and handling asynchronous processing.

Real-time database solutions

Some chat applications require real-time updates and synchronization across multiple clients. In such cases, specialized real-time database solutions like Firebase Realtime Database or Amazon DynamoDB Streams can be beneficial. These databases provide real-time data synchronization and can automatically notify clients of changes, facilitating real-time chat interactions.

Hybrid approaches

Depending on the requirements, a combination of databases may be used in a chat application. For example, using a relational database for user authentication and managing user profiles while employing a NoSQL database or message queue for storing and retrieving chat messages efficiently.

Solution for chat application


PostgreSQL, often referred to as “Postgres,” is a powerful and feature-rich open-source relational database management system (RDBMS). It is known for its robustness, extensibility, and adherence to SQL standards. Here are some key features and characteristics of PostgreSQL.


CockroachDB1 is an open-source distributed SQL database system designed to provide scalability, consistency, and high availability. It is inspired by Google’s Spanner database, which was developed to handle massive global-scale applications.


MongoDB is a popular open-source document-oriented NoSQL database that provides flexible and scalable data storage solutions. It is designed to handle unstructured and semi-structured data and offers high performance, horizontal scalability, and ease of development. Here are key features and characteristics of MongoDB.


Apache Cassandra2 is a highly scalable, distributed, and open-source NoSQL database designed to handle massive amounts of structured and unstructured data across multiple commodity servers while ensuring high availability and fault tolerance. Here are key features and characteristics of Cassandra.

Cassandra has many examples like Discord, Instagram Direct, Netflix, Spotify, old Facebook Messenger and old Twitter.


HBase is an open-source, distributed, column-oriented NoSQL database that is built on top of the Hadoop Distributed File System (HDFS). It provides a scalable, fault-tolerant, and consistent data storage solution for big data applications. Here are key features and characteristics of HBase

HBase is commonly used in scenarios where high scalability, fault tolerance, and real-time data access are required. It finds applications in areas like time-series data storage, sensor data processing, social media analytics, log analysis, and more. The tight integration with the Hadoop ecosystem makes it a valuable component of big data processing pipelines.

Facebook Messenger uses HBase for storing messages and user information. It also uses HBase for storing user activity logs and other data.

MySQL Vitess

MySQL Vitess is an open-source database clustering system for MySQL that provides horizontal scalability, sharding, and distributed query capabilities. It was originally developed by YouTube to address the challenges of scaling MySQL for large-scale applications. Here are key features and concepts related to MySQL Vitess.

MySQL Vitess is particularly useful for applications that require the scalability of sharding while maintaining MySQL compatibility. It can be beneficial for scenarios with rapidly growing data, high write and read workloads, and the need for online schema changes. Vitess integrates with MySQL and various application frameworks, making it easier to adopt and scale existing MySQL-based applications.

Slack uses MySQL Vitess for storing user data and chat messages. It also uses Vitess for handling real-time updates and notifications. 3