22/01/2023
As a web developer, you may have experience working with the popular MERN stack (MongoDB, Express.js, React.js, and Node.js) and may be wondering about the differences between MongoDB and PostgreSQL. Both MongoDB and PostgreSQL are popular open-source databases, but they have some key differences in terms of data model, scalability, performance, and features. In this article, we will explore the similarities and differences between MongoDB and PostgreSQL, and discuss the pros and cons of each database. By the end of this article, you will have a better understanding of when to use MongoDB and when to use PostgreSQL, and how to make an informed decision for your next project.
âī¸ Data Model: MongoDB is a document-oriented database, which means that it stores data in semi-structured format, typically in JSON-like documents. In contrast, PostgreSQL is a relational database, which means that it stores data in a structured format, using tables and rows.
âī¸ Scaling: MongoDB is designed to scale horizontally using a technique called sharding, which involves spreading the data across multiple servers. PostgreSQL can also be scaled horizontally, but it typically requires additional tools or extensions, such as pgpool, to achieve this.
âī¸ Performance: MongoDB is generally considered to have better performance when it comes to read and write operations on large amounts of unstructured data, while PostgreSQL is generally considered to have better performance when it comes to complex queries on structured data.
âī¸ Indexing: MongoDB supports secondary indexes, which can be used to improve query performance. PostgreSQL supports various types of indexes, such as B-tree, Hash, and GIN indexes, allowing for more flexibility in indexing.
âī¸ Concurrency: MongoDB uses a technique called "optimistic concurrency control" to handle concurrent access to the database, while PostgreSQL uses a technique called "multi-version concurrency control" (MVCC).
âī¸ ACID compliance: PostgreSQL is fully ACID compliant, meaning it has support for Atomicity, Consistency, Isolation and Durability. MongoDB on the other hand is not fully ACID compliant, but it has support for Atomicity at document level and consistency using transactions.
âī¸ Language Support: PostgreSQL supports a variety of languages for stored procedures and functions such as PL/pgSQL, PL/Tcl, PL/Perl, and more, MongoDB has its own query language, and also supports javascript for stored procedures.
âī¸ PostgreSQL also supports NoSQL like querying with its JSON and JSONB data types and functions, MongoDB is entirely a NoSQL Database.
âī¸ Community: Both MongoDB and PostgreSQL have large and active communities, but PostgreSQL has a longer history and more mature ecosystem. This means that there are more resources, tools, and libraries available for PostgreSQL, and it is generally considered to be more stable and reliable.
âī¸ Licensing: MongoDB is released under the Server Side Public License (SSPL) which is a variant of the AGPL. PostgreSQL is released under the PostgreSQL License which is a permissive open-source license. This means that MongoDB may be less suitable for some organizations that cannot use AGPL licensed software.
âī¸ Data Integrity: PostgreSQL supports advanced features such as foreign keys, and constraints, which allow you to enforce data integrity and consistency. MongoDB does not support foreign keys, but it does support document validation.
âī¸ Data Governance: PostgreSQL provides advanced features for data governance and compliance, such as auditing and row-level security, which can be used to restrict access to specific rows in a table based on certain conditions. MongoDB does not have built-in support for data governance and compliance, but it does have a feature called MongoDB Realm which provides some functionality for this.
âī¸ Text Search: PostgreSQL has a built-in text search feature, called Full Text Search, which allows you to perform complex text search queries. MongoDB does not have a built-in text search feature, but it does have a feature called text indexing, which allows you to perform basic text search queries.
âī¸ Analytics: PostgreSQL has built-in support for advanced analytics, such as window functions and user-defined aggregate functions. MongoDB does not have built-in support for advanced analytics, but it can be integrated with other analytics tools such as Apache Spark, which allows you to perform advanced analytics on your data.
Finally, MongoDB is better suited for high-performance, unstructured data storage and handling, while PostgreSQL is better suited for structured data and complex queries and transactions. Depending on the use case and requirements, either one can be a better fit.