Difference between PostgreSQL and MongoDB

Data moves between replicas in PostgreSQL and between partitions in MongoDB. Availability ensures that even during a server outage, there’s no data downtime. MongoDB uses primary node replication, which duplicates data into replica sets. A singular primary node receives the writes, and secondary nodes then replicate this data.

It makes queries execute faster as it’s in a serialization format that effectively archives JSON-like documents. Despite the popularity of NoSQL databases, relational databases continue to be relevant for various applications because of their robustness and strong querying abilities. In this YouTube video, I compare these two databases and discuss which one is more suitable for a project in 2023. In today’s digital era, data management has become a crucial aspect of businesses. With the vast amount of data that is generated every day, it is essential to have a robust database management system that can handle the complexity and scale of modern applications.

I want to read this e-book

PostgreSQL also outperforms or at worst, matches MongoDB for performance. MongoDB also offers an On-Premise pricing model with MongoDB Enterprise Advanced edition. In the modern world today, competition between companies is very common, especially when they are offering similar products. In the competitive field of Data Analytics, offering efficient products and services and having a majority customer share in the market does help determine the profit of the company.

One of the most pivotal features of relational databases that make writing applications simpler is ACID transactions. As far as the isolation levels within database transactions are concerned, PostgreSQL uses the read committed isolation level, by default. It also allows users to tune the read committed isolation level up to the serializable isolation level. It is built on a distributed, scale-out architecture and offers a comprehensive cloud-based platform for managing and delivering data to applications. MongoDB handles transactional, operational, and analytical workloads at scale.

Scalability

The signals may be received and decoded by anyone with a VHF antenna, including nearby vessels. AIS was designed to be a collision avoidance system for vessels and due to the purpose it serves and its technical characteristics, it was never meant to be centralized. However nowadays there are companies that gather AIS messages through satellites and terrestrial VHF stations around the globe in their databases.

The challenge of using a relational database is the need to define its structure in advance. Changing structure after loading data is often very difficult, requiring multiple teams across development, DBA, and Ops to tightly coordinate changes. In a relational database, the data in question would be modeled across separate parent-child tables in a tabular schema. This means that updating all the records at once would require a transaction.

MongoDB vs PostgreSQL

Mongo RealmDB is available free of charge to all Atlas users for evaluation and light usage, enabling developers to build and release mobile applications. Unlike MongoDB, PostgreSQL depends on a scale-up strategy (vertical scaling) for data volumes and scaling writes. It’s performed by adding more hardware resources like disks, CPUs, and memory to an existing database node. However, the denormalization process usually causes high memory consumption when previously normalized data in a database is grouped to increase performance. MongoDB can deal with both normalized and denormalized data models (also known as embedded models). Replication is the process of creating a copy of the same dataset on more than one server.

• This means it’s easy for developers to pick up, learn, and put to good use.
• If you require a modern database to process data from various sources and in various formats, then go for MongoDB.
• You can select the database based on the development of the application and the language you intend to use in the application.
• PostgreSQL’s focus on data consistency and reliability makes it an ideal choice for applications demanding rigorous transactional support and relational modelling.
• But MongoDB might be a poor fit if you have a large number of incumbent apps based on regional data models and teams that have experience with SQL only.

However, if you want to store and process a range of data in different formats and in real or near-real time, document databases like MongoDB will suit your business requirements better. This flexibility of document-based MongoDB helps database developers to collect and store data from diverse sources. It also helps to work with changing requirements that need to be reflected in the mongodb vs postgresql which is better stored document data and is a norm in software applications today. Scalability refers to a database’s ability to handle increasing data and users without sacrificing performance. Both MongoDB and PostgreSQL are scalable but achieve it in different ways. MongoDB scales horizontally by sharding data across multiple nodes, which allows it to handle large amounts of data and traffic.

Hire vetted developers with DevTeam.Space to build and scale your software products

PostgreSQL uses MVCC, data snapshots, flexible isolation levels, and deadlock detection to provide concurrency. While MongoDB doesn’t have the same level of community maturity, it does offer drivers for many programming languages. There is lots of community and aid to help you interact with MongoDB using one of your preferred programming languages. It has a strong open-source community with lots of PostgreSQL support libraries, tools, extensions, and general support available. PostgreSQL also provides various index types, including B-tree, hash, GIN, GiST, and Sp-GiST. MongoDB organizes each document into collections, with each having a unique ObjectId, which you use to identify a document.

At the start of development projects, it’s common for project leaders to have a clear understanding of the use case — but not of the specific features their users need in an application. MongoDB and PostgreSQL are both reputable databases that have their advantages and disadvantages. What is most important is how your data is going to be used, what structure will it have, and how will your application scale.

PostgreSQL vs. MongoDB Feature Comparison

It assumes there are no conflicts between most concurrency write operations, which allows people to modify data at the same time without acquiring locks. It also creates a new revision ID for the document, which allows multiple documents with the same data to exist simultaneously. PostgreSQL uses an SQL variant, called Postgres SQL, as its query language. Although similar to SQL, it has additional features like an extensible type system, functions, and inheritance. However, PostgreSQL is still compatible with standard SQL, so you can use SQL queries as well. Migrating to a NoSQL document database can be a challenge if you have a large data model.

It allows us to use tables and columns to reduce redundancy in data, minimize anomalies in data modification, and simplify queries. A term coined for database systems (i.e. VoltDB and MemSQL) that combines the best aspects of relational databases (ACID) with the efficiency and horizontal scalability of NoSQL databases. MongoDB can work best when integrated into an analytics platform, as MongoDB’s speed provides dynamic performance that can help track the user’s behavior in real time. Before adding the data, the database schema must be built to get a clear understanding of the data relationships to process the queries. By storing data in fields such as nested subdocuments and arrays, related information in JSON documents can be stored together for quick query access through the MongoDB query language. MongoDB also supports database transactions across multiple documents allowing bits of related changes to be rolled back or committed as a group.

All About PostgreSQL Remote Access Under Plesk – Full Guide

PgSQL is used to access, manipulate, and store data in the PostgreSQL database. The video ends with a summary of the main points and a recommendation for choosing a database management system for a project in 2023. I suggest that PostgreSQL is a better option than MongoDB for most use cases because it has more features, better performance, and lower cost.