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Farewell MongoDB: 5 reasons why you only need PostgreSQL

Discuss the reasons why you should consider PostgreSQL over MongoDB for your next project.

Yijun

Developer

6/27/20243 min read

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Introduction

In the database world, MongoDB and PostgreSQL are both highly regarded choices. MongoDB, a popular NoSQL database, has gained widespread popularity since its inception in 2009 due to its flexible document model and ease of use. PostgreSQL, on the other hand, is a long-standing relational database that has been continuously evolving and innovating since its first release in 1996, becoming one of the most feature-rich and advanced open-source databases available.

Over time, database requirements have changed significantly. Enterprises need to handle not only structured data but also the growing volume of unstructured data. Additionally, data consistency, scalability, and performance have become increasingly important. In this context, PostgreSQL has been closing the gap with MongoDB through continuous innovation and improvement, even surpassing it in many aspects. Let's explore why PostgreSQL might be a better choice than MongoDB in most cases.

Reason 1: The perfect combination of SQL and NoSQL

One of PostgreSQL's greatest strengths is its ability to seamlessly combine SQL and NoSQL features. With robust JSON support, PostgreSQL allows users to handle both structured and unstructured data within the same database.

PostgreSQL's JSONB data type provides efficient JSON document storage and querying capabilities, comparable to MongoDB. In fact, according to benchmarks by EnterpriseDB, PostgreSQL's performance in handling JSON data can even surpass MongoDB. This means users can enjoy the powerful features of a relational database while also benefiting from the flexibility of a NoSQL database.

Reason 2: More powerful and flexible join operations

When dealing with related data, the performance and flexibility of join operations are crucial considerations. PostgreSQL clearly outperforms MongoDB in this area:

Execution Methods: PostgreSQL uses mature relational database join algorithms such as nested loop join, merge join, and hash join. The query optimizer automatically selects the optimal join strategy. In contrast, MongoDB primarily uses the $lookup aggregation operation to perform joins, which is essentially a nested loop join.
Performance: In most scenarios, especially when handling complex multi-table joins, PostgreSQL's performance is significantly better than MongoDB. MongoDB's performance can degrade considerably when dealing with complex join operations, as it only supports nested loop joins, whereas PostgreSQL can choose more efficient hash joins and merge joins.
Flexibility: PostgreSQL supports various types of joins (inner join, outer join, cross join, etc.), enabling it to handle complex relational queries. MongoDB's join capabilities are relatively limited, mainly suitable for simple one-to-many relationships.
Adaptability to Data Model Changes: When the data model changes (e.g., from a one-to-many relationship to a many-to-many relationship), PostgreSQL only requires modifications to the table structure and query statements, with relatively minor changes to the application. In MongoDB, such changes may necessitate redesigning the document structure and making extensive modifications to the application.

While MongoDB may be simpler and more straightforward in certain specific scenarios, PostgreSQL offers more powerful and flexible join capabilities when dealing with complex related data. For applications that may require frequent complex join operations, PostgreSQL is usually the better choice.

Reason 3: Superior data consistency and integrity

MongoDB has made significant progress in data consistency and transaction support since version 4.0, introducing multi-document ACID transactions and continually improving this feature. For many applications, MongoDB now offers reliable transaction support.

However, PostgreSQL still holds a distinct advantage in this area. As a mature relational database, PostgreSQL has always provided full ACID (Atomicity, Consistency, Isolation, Durability) compliance out of the box. Its strong consistency model, deeply ingrained in its architecture, ensures data remains consistent and reliable under all circumstances, including system crashes or power failures. While MongoDB's improvements are commendable, PostgreSQL's time-tested approach to data consistency and integrity continues to be a gold standard, especially for applications dealing with sensitive or mission-critical data.

Reason 4: Excellent scalability and performance

As data volumes grow, scalability and performance become increasingly important. While MongoDB has long been considered advantageous in handling large-scale datasets, PostgreSQL has made significant strides in this area.

PostgreSQL, with features like table partitioning, parallel query execution, and efficient indexing, can effectively handle large-scale datasets. Additionally, PostgreSQL's horizontal scalability is continually improving, making it capable of meeting the needs of most enterprise-level applications. So you can rely on PostgreSQL to scale your application as it grows.

Reason 5: Rich functional ecosystem

PostgreSQL boasts a very rich functional ecosystem, which is a significant advantage over MongoDB:

Powerful Full-Text Search: PostgreSQL's built-in full-text search capabilities can meet the needs of most applications without requiring an additional search engine.
Geospatial Data Support: Through the PostGIS extension, PostgreSQL provides robust Geographic Information System (GIS) capabilities, making it easy to handle geospatial data.
Advanced SQL Features: PostgreSQL supports advanced SQL features such as window functions and Common Table Expressions (CTEs), simplifying the writing of complex queries.
Extensive Extension Plugins: In addition to PostGIS, there are numerous extensions like TimescaleDB for time-series data processing and pgvector for vector search, greatly expanding PostgreSQL's application scope.

Conclusion

PostgreSQL, with its powerful SQL and NoSQL capabilities, superior data consistency, excellent scalability and performance, and rich functional ecosystem, can surpass MongoDB in most use cases. Although migrating from MongoDB to PostgreSQL may require some effort, it is usually worthwhile in the long run as it can simplify the technology stack and improve data management efficiency and reliability.

Actionable advice

If you are considering choosing a database or evaluating your current database solution, it is recommended to carefully assess whether PostgreSQL can meet your needs. You can start learning PostgreSQL in-depth from the following resources:

Remember, choosing the right database solution can bring long-term benefits to your application, including higher performance, better maintainability, and lower total cost of ownership.

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Introduction#

Reason 1: The perfect combination of SQL and NoSQL#

Reason 2: More powerful and flexible join operations#

Reason 3: Superior data consistency and integrity#

Reason 4: Excellent scalability and performance#

Reason 5: Rich functional ecosystem#

Conclusion#

Actionable advice#

Introduction#

Reason 1: The perfect combination of SQL and NoSQL#

Reason 2: More powerful and flexible join operations#

Reason 3: Superior data consistency and integrity#

Reason 4: Excellent scalability and performance#

Reason 5: Rich functional ecosystem#

Conclusion#

Actionable advice#

Introduction

Reason 1: The perfect combination of SQL and NoSQL

Reason 2: More powerful and flexible join operations

Reason 3: Superior data consistency and integrity

Reason 4: Excellent scalability and performance

Reason 5: Rich functional ecosystem

Conclusion

Actionable advice

Introduction

Reason 1: The perfect combination of SQL and NoSQL

Reason 2: More powerful and flexible join operations

Reason 3: Superior data consistency and integrity

Reason 4: Excellent scalability and performance

Reason 5: Rich functional ecosystem

Conclusion

Actionable advice