MongoDB vs PostgreSQL: Complete Comparison in 2022

MongoDB and PostgreSQL are ACID compliant but achieve it in slightly different ways. MongoDB uses multi-document transactions, which allows you to perform transactions on multiple documents in a single operation. PostgreSQL, on the other hand, supports traditional SQL transactions, which are more familiar to developers. They have also highlighted that, at present, there are no relational databases that fully conform to that standard. MongoDB offers a modern selection of cybersecurity controls and integrations for both its cloud and on-site versions. This features strong security paradigms such as client-side, field-level encryption — this enables users to encrypt data before sending it to the database via the network.

Instead of storing data like documents, PostgreSQL stores it as Structured objects. This article provides you with a comprehensive analysis of both databases and highlights the major differences between them to help you make the MongoDB vs PostgreSQL decision easy. It also provides you a brief overview of both databases along with their features.

Complex Data Types:

MongoDB has the potential for ACID compliance, while Postgres has ACID compliance built-in. ACID (atomicity, consistency, isolation, durability) are principles or components that work toward data validity, especially in databases intended for transactional workflows. So, now that we know what each database has to offer, we need to determine when to choose each depending on the data, organization, and requirements in question.

Developers can decide what’s needed in the application and change it in the database accordingly. PostgreSQL is a rock solid, open source, enterprise-grade SQL database that has been expanding its capabilities for 30 years. Everything you would ever want from a relational database is present in PostgreSQL. MySQL is definitely not the best choice for RDBMS or ORDBMS applications. Since Oracle’s acquisition of MySQL, adoption of MySQL has significantly declined, and development progress in the open-source space has taken a hit as well, inviting criticism from MySQL users.

Summary of differences: MongoDB vs. PostgreSQL

Furthermore, you can also update related data in a single atomic write operation while applications issue fewer queries to complete common operations. Documents in MongoDB for the embedded data model must be smaller than the maximum BSON document size (16 MB). On the other hand, MongoDB allows you to store data in any structure that can be quickly accessed by indexing, no matter how deeply nested in arrays or subdocuments. Partitioning and sharding are essentially about breaking up large datasets into smaller subsets. Sharding implies that the data is stored across multiple computers while partitioning groups this data within a single database instance. MongoDB has a document model, making collaboration and development easier and faster to implement.

This makes it ideal for situations where data needs to be real-time or near real-time, thereby enabling companies to get a holistic view of their business in real-time and improve data optimization. Foreign keys allow us to keep our data normalized by referencing an object from one table in another so the second table has access to the first table’s keys and values. It’s a trusted choice for enterprise-level applications and situations where the reliability of the database system is paramount.

Does MongoDB support ACID transactions?

It is a document-oriented database, storing data as documents instead of tables and rows like traditional relational databases. Think of it like a digital filing cabinet, where each document is unique and contains all the information needed to access and manipulate it. It’s been around since the ’80s and has evolved into a robust and stable database management system. PostgreSQL is a relational database that stores data in tables and rows with relationships between them. It offers a rich set of features for complex queries and supports advanced data types like arrays and JSON. When you build a SQL database, you have primary and foreign keys set up to link records across tables.

Launched in 2007, MongoDB now serves some of the world’s biggest companies, including EA, eBay, and Shutterfly. MongoDB has very fast task fulfillment, in particular, thanks to the fact that the data is only semi-structured. According to various reviews, it is one of the faster solutions on the market, even when dealing with huge volumes of data on a regular basis.

Difference between MongoDB and PostgreSQL

Their structure provides flexible schemas, and they can be scaled easily. PostgreSQL uses the relational database model that depends on storing data within tables and utilizing the structured query language (SQL) for database access. It has a large object facility, which provides stream-style access to user data that is stored in a special large-object structure.

PostgreSQL, often referred to as « Postgres, » is a robust open-source relational database management system. It excels in data integrity, consistency, and powerful SQL capabilities, making it a preferred choice for applications where structured data and complex queries are essential. PostgreSQL supports various data types, including JSON, and offers advanced indexing techniques, making it versatile for different data requirements. mongodb vs postgresql MongoDB, a NoSQL database, shines in its adaptability, accommodating evolving data models and offering remarkable scalability. In contrast, PostgreSQL, a robust relational DBMS, excels in data integrity, SQL capabilities, and security. It is favored for applications demanding structured data, complex queries, and stringent data consistency, making it a top pick for industries like finance and healthcare.

Differences Between Relational (PostgreSQL) and Non-Relational (MongoDB) Databases

You can make consecutive data types, functions, and even programming languages run inside the database. In collation, PostgreSQL is open source and has a vibrant people of contributors that continuously enhance its performance and add new features. Whether residence an easy web app or a complex data warehouse, PostgreSQL is a solid choice that won’t let you down. The query language allows for deeply nested queries and filtering on embedded arrays. This flexibility aligns with MongoDB’s schema-less philosophy, enabling developers to navigate and extract data from documents with dynamic structures.

On the other side of the spectrum, we have PostgreSQL, a venerable open-source relational database that embraces the traditional SQL paradigm. It excels in handling structured data, embodying a rock-solid foundation of ACID (Atomicity, Consistency, Isolation, Durability) compliance. PostgreSQL, often referred to as Postgres, is a powerful open-source relational database management system. It stands out for its adherence to SQL standards and emphasis on data integrity. MongoDB can be a good choice if you want your database to be highly scalable and have a high computation & processing power. It can also be used if users lack programming skills as it is very easy to learn and does not follow the traditional SQL syntax.

Jointhe community

MongoDB has enjoyed widespread adoption as it has become the biggest modern database — it’s considered the go-to database by many developers. Due to the dedicated MongoDB community and engineering, it’s become a comprehensive platform that serves developers’ needs to an exceptional degree. Growing databases are supported by an ecosystem made up of many services, partners, integrations, and other relevant products.

• PostgreSQL stores the information about the columns, and tables, along with information regarding the data types, functions, and access methods present.
• It’s open source and usually chosen alongside other relational databases such as MySQL, but it works with object-based data rather than traditional table linking.
• PostgreSQL is getting popularity because of its structure and wide range of use.
• BSON allows for certain data types that are not used with regular JSON, such as long, floating-point, and date.
• MongoDB is popular among developers due to its flexible schema and use of JSON-like documents.
• The transcript is the copying of data from one database to another to confirm high availability and redundancy.