17 min readUpdated Dec 5, 2023

Ultimate guide: Best databases for NodeJS apps

Ultimate guide: Best databases for NodeJS apps
Hamza ShahabHamza Shahab

NodeJS is a JavaScript-based backend framework for web applications. It enables fast, scalable, and efficient development with high concurrency and data streams.

Choosing the right database for NodeJS applications is a challenge for developers. A database should store and manage the data, handle the volume and velocity of data, provide the features and functionality you need, and be compatible, easy, secure, and reliable with NodeJS.

NodeJS applications can use different types of databases, such as:

  • Relational databases: These databases store data in tables with schemas and relationships. They are good for complex queries, transactions, and analysis. Some examples of relational databases are MySQL, PostgreSQL, and Oracle.
  • NoSQL databases: These databases store data in various formats, such as documents, key-value pairs, graphs, or columns. They are good for large and unstructured data, horizontal scaling, and high availability. Some examples of NoSQL databases are MongoDB, Redis, Cassandra, and Neo4j.
  • Realtime databases: These databases provide realtime synchronization and updates between the server and the clients. They are good for realtime collaboration, communication, and interaction. Some examples of realtime databases are Firebase, RethinkDB, and Couchbase.

The best database for a NodeJS application depends on many factors, such as the data type, size, and complexity, the performance and scalability requirements, the environment, and the budget, and developer preference. This article will explore some of the best NodeJS databases for creating amazing web applications.

Factors to consider when choosing a database for NodeJS

To choose a database for your NodeJS app, consider these factors:

  • Data model and query needs: What kind of data will your app store and manipulate? What kind of queries will your app perform on the data? You may need a relational, NoSQL, or realtime database depending on your data model and query needs.
  • Performance, scalability, and reliability: How well can the database handle concurrent requests and data streams? How easy can it scale up or down? How often does it experience downtime or data loss? How secure is it from unauthorized access or attacks?
  • Compatibility and interoperability: Check the database's compatibility and interoperability with NodeJS frameworks and libraries. See how easy it is to set up and use the database with NodeJS, and how well it supports NodeJS features and functionality. Find out the quality and availability of the tools that connect NodeJS and the database.

These factors will help you determine which NodeJS database best meets your project requirements.

Comparing SQL and NoSQL databases

SQL and NoSQL are two different ways to store and manage data in databases. SQL is a standard language for relational databases that store data in tables with predefined schemas. NoSQL is a term for non-relational databases that store data in various formats and support different query languages.

Let's take a look at both types of databases and how they differ in a bit more detail.

  • Data model: SQL databases store data in tables with fixed schemas and relationships. NoSQL databases store data in various formats, such as documents, key-value pairs, graphs, or columns, with flexible or dynamic schemas.
  • Query language: SQL databases use SQL as the standard language for data access and manipulation. SQL is a declarative and expressive language that supports complex queries, transactions, and data analysis. NoSQL databases use different query languages, depending on the data format. Some NoSQL query languages are SQL-like, while others are more procedural and specific. NoSQL query languages support simple queries, aggregation, and map-reduce operations.
  • Performance, scalability, and reliability: SQL databases are optimized for performance, as they can handle complex queries and transactions efficiently and accurately. SQL databases also ensure data consistency and integrity, as they follow the ACID properties. However, SQL databases may have limited scalability, as they require vertical scaling or sharding, which can be costly and complex. NoSQL databases are optimized for scalability, as they can handle large and unstructured data easily and quickly. NoSQL databases also ensure data availability and fault tolerance, as they follow the BASE properties. However, NoSQL databases may compromise data consistency and integrity for speed and flexibility.

Advantages and disadvantages of SQL and NoSQL databases

The advantages and disadvantages of each approach are:

  • SQL databases: The advantages of SQL databases are that they provide a standard and powerful query language, support complex queries and transactions, ensure data consistency and integrity, and offer rich features and functionality. The disadvantages of SQL databases are that they require a fixed and rigid schema, need help in handling large and unstructured data, and have limited scalability and flexibility.
  • NoSQL databases: The advantages of NoSQL databases are that they provide a flexible and dynamic data model, support large and unstructured data, and offer high scalability and availability. The disadvantages of NoSQL databases are that they have different and diverse query languages, support simple queries and operations, compromise data consistency and integrity, and lack some features and functionality.

Choosing between SQL and NoSQL for your NodeJS app

To decide which one suits your use case better, you should consider the following questions:

  • What is the type, size, and complexity of your data?
  • What are the performance and scalability requirements of your application?
  • What features and functionality does your application need from the database?
  • What are the development and deployment environments and preferences of your developers?

Depending on your answers, you may choose an SQL database, a NoSQL database, or a hybrid solution that combines both approaches. In the next section, we will explore some of the best NodeJS databases that you can use for your application.

Top six NodeJS databases

SQL databases

PostgreSQL: A powerful database for NodeJS

Overview: PostgreSQL is a powerful open source database that supports many SQL and advanced features. It can handle various types of data, such as JSON, geospatial data, etc, and also allows full text search. PostgreSQL is suitable for data analytics, geospatial applications, and complex queries.


  • High performance: It has high performance and various optimization techniques, such as indexing, partitioning, query planning, and caching.
  • Rich feature set: It has a rich feature set and supports many SQL features and advanced features, such as full-text search, foreign data wrappers, materialized views, triggers, stored procedures, and inheritance.
  • Extensive documentation: PostgreSQL has comprehensive and detailed documentation that covers all aspects of the database system, such as installation, configuration, administration, development, and troubleshooting. The documentation is available online and offline and in multiple languages.
  • Community support: It has a large community support, and is available online and offline and in multiple languages.


  • Complex installation and configuration: It requires  complex installation and configuration, as it has many dependencies, options, and settings, and may require additional tools and software, such as pgAdmin.
  • Steep learning curve: PostgreSQL is a powerful and versatile database system that supports many SQL features and extensions. However, it also has a steep learning curve for beginners or users who are not familiar with SQL or object-relational databases.
  • Potential licensing issues: PostgreSQL is licensed under the PostgreSQL License, which is a liberal open source license that is similar to the BSD or MIT licenses. However, some other software or platforms may have different or incompatible licenses that could pose legal challenges or conflicts when used with PostgreSQL. For example, some software or platforms may require that any derivative work based on PostgreSQL must also be licensed under the same or compatible license, or that any modification or enhancement to PostgreSQL must be disclosed or contributed back to the original project. These requirements can limit the freedom and flexibility of PostgreSQL users and developers, and may violate the PostgreSQL license.
  • Limited horizontal scalability and availability: PostgreSQL has limited horizontal scalability and availability, as it does not support native sharding or clustering, which are techniques for distributing and partitioning data across multiple servers.

Use cases

  • Data analytics: PostgreSQL is a popular choice for organizations that need to perform data analysis and reporting on large and complex data sets, such as business intelligence, data warehousing, or data mining.
  • Geospatial applications: Another use case of PostgreSQL is geospatial applications. These are applications that need to store and manipulate geospatial data, such as coordinates, shapes, and distances. PostgreSQL can use various extensions, such as PostGIS, that add additional functionality, such as spatial indexing, geometry operations, and geocoding.
  • Complex queries: PostgreSQL can be used to handle complex queries efficiently and flexibly. Complex queries are queries that involve multiple tables, joins, subqueries, and aggregations, and that require a high level of expressiveness and logic.

MySQL: Ideal for fast and efficient data processing

Overview: MySQL is a popular open source database that stores data in tables with predefined schemas. It is mainly used for web development and e-commerce, as it can handle fast and efficient data processing. MySQL can support various features and functions that are essential for web development and e-commerce, such as, relational data model, SQL language and high availability.


  • Easy to set up and use: It is easy to set up and use, with a simple user interface and documentation.
  • High availability: It provides high availability and fault tolerance, with various replication and backup options.
  • Compatibility with many platforms and languages: It is compatible with many platforms and languages, such as Linux, Windows, Java, and PHP.


  • Limited scalability: MySQL mainly supports vertical scaling or sharding, which can limit its ability to handle large and complex data sets. However, this can be costly and complex, as it requires hardware upgrades, downtime, or migration.
  • Lack of advanced features: MySQL lacks some advanced features that other database systems offer, such as full-text search, materialized views, and inheritance. MySQL also does not fully support the ACID properties, which are guarantees that ensure the reliability and integrity of the data.
  • Prone to SQL injection : MySQL faces some security challenges and risks that require proper security measures and best practices to protect the data and the application from unauthorized access or malicious attacks. Some of the common security threats that can affect MySQL are SQL injection, denial-of-service, and brute-force attacks, which can manipulate, compromise, or overload the database server.
    Use cases
  • Popular web applications: MySQL is widely used for developing web applications that need to store and manipulate structured data, such as text, numbers, dates, or images. Some examples of web applications that use MySQL are Facebook, Twitter, YouTube, and Wikipedia.
  • Blogs: Platforms like WordPress, Drupal, and Joomla, that need to store and display text, images, videos, or audio.
  • Online stores: Platforms including Shopify, Magento, and WooCommerce, that need to store and process product information, customer orders, payment details, and inventory data.

SQLite: Lightweight and portable database solution

Overview: SQLite is a database engine that can store and manipulate data in a single file, without requiring any server or configuration. SQLite is an open source, zero-configuration, self-contained, and transactional database that supports many SQL features and advanced features.


  • Lightweight: It is lightweight, with a low memory footprint and a minimal disk space requirement.
  • Portable: It can run on various platforms and languages, and can be easily copied, moved, or shared.
  • Self-contained: It is self-contained, as it does not depend on any external components or services, and supports various features, such as transactions, data integrity, and encryption.


  • Limited concurrency: SQLite uses a file-level locking mechanism and does not support multi-user or network access - this can limit concurrency.
  • Limited functionality: SQLite has limited functionality, as it does not support some features. For example, SQLite does not support stored procedures, which are routines that can contain procedural logic and parameters. SQLite also does not support full-text search, which is a technique for fast and accurate search of natural language terms in large text fields.

Use cases:

  • Local development: SQLite is an embedded database system, which means that it does not require a separate database server to operate. SQLite’s database is a single file on disk, which can be easily copied, moved, or shared across different systems or platforms.
  • Testing: SQLite can be used to perform unit testing or integration testing on applications or software that use databases, as it can create and populate test databases with mock data quickly and easily. For example, SQLite is used by testing tools, such as PHPUnit, pytest, and RSpec, as a testing database for database-related functionality and logic.
  • Prototyping: SQLite can be used to create and demonstrate prototypes or proofs of concept that use databases, as it can create and manipulate data simply and conveniently, without any installation or configuration. For example, SQLite can be used to prototype database-driven applications and interfaces, such as web apps, mobile apps, chatbots, or dashboards, by using mock data or sample data sets.

NoSQL databases

MongoDB: Handling unstructured data for dynamic apps

Overview: MongoDB is an open source database that stores data in JSON-like format. It is mainly used for web applications that require high performance, scalability, and flexibility, as it can handle large and complex data, as well as provide fast and agile data processing.


  • Flexible schema: It has a flexible schema, as it allows users to store and manipulate data in various shapes and sizes, and change the data structure and content at any time.
  • High scalability: It has high scalability and availability, as it supports various replication and sharding options, as well as various cloud platforms and services. Sharding is the process of distributing and partitioning the data across multiple servers or clusters, which enables horizontal scaling, load balancing, and performance optimization.
  • Performance: It has high performance and efficiency, as it can store and access data in a binary format, and use various indexing and caching techniques.
  • Hosted Version: MongoDB also offers a hosted version, called MongoDB Atlas, which is a fully managed cloud service that provides various features and benefits, such as security, backup, monitoring, and automation.


  • Partial join support : It does not support joins, foreign keys, or transactions, which are operations or constraints that combine or group data from multiple collections or documents in the same way as a relational database. However, MongoDB provides a limited join functionality through the $lookup aggregation stage, which allows documents from two collections to be combined based on a common field or expression. The $lookup stage can perform left outer join, uncorrelated subquery, or equality match operations, but it cannot perform inner join, outer join, or cross join operations.

Use cases:

  • Dynamic web applications: These are web applications that need to store and manipulate various types of data, such as text, images, videos, or audio. MongoDB can handle heterogeneous and dynamic data, as well as provide fast and flexible data processing.
  • Social media platforms: These are web applications that need to handle large and unstructured data, such as user profiles, posts, comments, likes, shares, or followers. MongoDB can scale horizontally and vertically, as well as support realtime updates and notifications.
  • Realtime analytics platforms: These are web applications that need to perform realtime analytics and reporting on large and complex data sets, such as web traffic, user behavior, or business metrics. MongoDB can perform complex queries and aggregations in real time, as well as integrate with various tools and frameworks for data analysis and visualization.

Firebase Realtime Database (RTDB): Enabling realtime communication

Overview: RTDB is a cloud-hosted, NoSQL database that syncs data in realtime across devices. It is a service by Firebase, a backend as a Service (BaaS) platform for mobile and web apps. RTDB can enable realtime communication, interaction, and collaboration for various types of web applications such as  realtime chat apps, online games, and collaborative tools.


  • Ease of installation: It is easy to get started , as it does not need any server-side code or some configuration, and has a simple API and various SDKs and libraries.
  • Low latency: RTDB has the ability to sync data in realtime across devices, which means that any changes made to the data on one device are immediately reflected on other devices. RTDB uses WebSocket protocol and a JSON-like format to sync data in realtime, which are faster and more efficient than HTTP protocol and XML format.
  • Offline support: It has offline support and resilience, as it caches data locally and syncs data automatically when online, and supports various conflict resolution and synchronization strategies.


  • Pricing model: It has a pricing model that may be costly and unpredictable, as it charges users based on the number of connections, the amount of data stored, and the amount of data downloaded.
  • Limited querying capabilities: It has limited querying capabilities, as it does not support complex queries, SQL, or other query languages, and has some limitations in supporting some data types and operations.
  • Security rules complexity: It has security rules complexity, as it requires users to write and maintain security rules in a custom language, and does not provide any graphical tools or interfaces to manage and monitor them.

Use cases:

  • Realtime chat apps: RTDB can store and sync chat data across multiple devices, as well as provide features such as online presence, typing indicators, read receipts, and push notifications.
  • Online games: RTDB can handle game logic, state, and data, as well as support features such as multiplayer, matchmaking, leaderboards, and achievements.
  • Collaborative tools: RTDB can store and sync project or document data across multiple devices, as well as provide features such as collaborative editing, commenting, versioning, and access control.

CouchDB: Supporting mobile apps and offline scenarios

Overview: CouchDB is an open source database that stores data in JSON-like format. It is mainly used for mobile applications, offline-first scenarios, and peer-to-peer networks, as it supports replication and synchronization over HTTP.


  • Distributed architecture: It has a distributed and decentralized architecture, as it allows users to create and manage multiple copies or replicas of the database on different devices or locations, and control and customize how and when the data is replicated and synchronized.
  • Fault tolerance: It has fault tolerance and resilience, as it can handle network failures, device crashes, or data conflicts, without losing or corrupting the data, and restore and recover the data, if needed.
  • Conflict resolution: It has conflict resolution and consistency, as it can detect and resolve data conflicts that may arise due to concurrent updates or replication, and choose and apply the best solution for their data.


  • Slow performance: CouchDB operations can sometimes be slower and less efficient due to its use of HTTP protocol and a map-reduce framework, but this depends heavily on the nature of the specific use case in question.
  • Memory consumption: CouchDB can consume more memory and disk space than other database systems due to its data format and storage model. CouchDB stores and transmits data in a text format called JSON, which is a human-readable and flexible data format, but also more verbose and larger than binary formats. CouchDB also stores multiple revisions and attachments of the data, which can enable version control and conflict resolution, but also increase the size and complexity of the data.
  • Partial transaction support: CouchDB supports transactions and the ACID properties for individual document updates, but not for multi-document operations. This means that CouchDB can ensure the reliability and integrity of the data for single document operations, such as create, update, delete, or read, but not for operations that involve multiple documents, such as join, group, or aggregate.

Use cases:

  • Mobile applications:  These are web applications that need to store and manipulate data locally on the device, and sync data remotely with the server or other devices, over HTTP. CouchDB can provide offline support and resilience, as it caches data locally and syncs data automatically when online, and supports various conflict resolution and synchronization strategies.
  • Offline-first scenarios: These are web applications that need to support users who may have intermittent or no network connectivity, and provide data availability and accessibility. CouchDB can store and sync data across multiple devices or locations, over HTTP, and allow users to access and modify the data even when offline. Some of the offline-first scenarios that can benefit from using CouchDB are disaster relief, health care, and education.
  • Peer-to-peer networks: These are web applications that need to enable direct and decentralized communication and collaboration among the users and the devices, without relying on any central server or authority. CouchDB can encrypt and authenticate data, as well as control data access and sharing, over HTTP, and provide data security and privacy.

Wrapping up

That’s it for our guide on the best NodeJS databases. We hope you learned something valuable from this article and gained a better understanding of:

  • How NodeJS can help you create fast and scalable web applications.
  • What are the advantages and disadvantages of using NodeJS with databases?
  • What are the different types of databases that you can use with NodeJS?
  • How to choose the right database for your NodeJS project based on your needs and goals?
  • What are some of the top NodeJS databases that you can try today?

To learn more about NodeJS, databases, or realtime technologies, and to join our community follow us on Twitter and join the conversation on Reddit.

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