Comparison of JOINS: MongoDB vs PostgreSQL

It has sky-high user satisfaction and is the preferred tool for database professionals around the world. Customers include Tesla, Apple, Facebook, Deutsche Bank, NASA, and 25,000 others in 145 countries. Live resharding allows users to change their shard keys as an online operation with zero downtime. Please follow this link to learn about the features of mongodb.

MongoDB vs PostgreSQL

The basic idea behind atomicity is that it supports a transaction paradigm. Either a transaction fails completely or succeeds completely, such as a transfer on funds from one account to another. On the other hand, while PostgreSQL is easy to install and is adaptable to almost all platforms, its efficiency may differ from platform to platform. Moreover, it doesn’t have revising tools or reporting instruments that could show the current condition of the database. You may have to check the database continuously if something doesn’t go as planned to avoid noticing a failure when it’s too late.

Perform ETL to PostgreSQL and MongoDB with

You may lose some data that means, however it is often smart for users that are less disturbed concerning dogging their data. PostgreSQL may be a smart relative dB that additionally offers a number of the advantages of a document model. Learn more about them, how they differ, and how MongoDB vs PostgreSQL to determine which one is right for you. Navicat for PostgreSQL is an easy-to-use graphical tool for PostgreSQL database development. DbVisualizer is equipping database professionals with the tools they need to build, manage and maintain state-of-the-art database technologies.

NoSQL databases are non-tabular, and they vary based on their different data models, such are document, wide-column, key-value, or graph. 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 for database access. SQL commands can be entered using the PostgreSQL terminal psql. It has a large object facility, which provides stream-style access to user data that is stored in a special large-object structure.

Machine Learning vs. AI

They also have many features that distinguish them from one another. Is a schema-free document high-performance database offering both free and paid plans. As a document database, MongoDB has a different structure and syntax than the traditional RDMS . As we said at the outset, the question is not “MongoDB vs PostgreSQL? ” but “When does it make sense to use a document database vs a relational database? ” because each database is the best version of its particular database format.

The right answer for your needs is based of course on what you are trying to do. Our goal in this article is to help to explain the personality and characteristics of each of these databases so you can better understand whether it meets your needs. MongoDB has the community support forums and other online sites like StackOverflow and severs fault. PostgreSQL has a wide range of community forums and commercial support as well.

It’s capable of powering massive applications regardless of it being measured by data sizes or users. 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 .

Plus, you need to comply with data governance frameworks when moving data from one location to another or you could face hefty penalties. Other data integration methods like ELT and ReverseETL can be just as challenging if you lack a large data engineering team. One of the most important parts of the function of any company is a secure database. With phishing attacks, malware, and other threats on the rise, it is essential that you make the right choice in order to keep your data safe and process it effectively. However, it can be extremely difficult to choose among the wide variety of database solutions on the market today.

Features of mongodb vs PostgreSQL

So far, a number of databases have been developed; choosing the appropriate one for our operating system may be a bit confusing because of the different advanced qualities every database has. In this blog, let us compare the databases PostgreSQL, MySQL and MongoDB. You could potentially use either MongoDB or PostgreSQL for any development project that you must design and build. If not implemented correctly, both NoSQL and SQL databases could cause bottlenecks and hinder performance.

This also means that the database can only scale as much as the machine running it. It was programmed in C, one of the most popular programming languages. PostgreSQL offers community support and only offers additional paid support options through certain other companies. As PostgreSQL handles relational database, it is object-oriented in nature. In MongoDB, all the contents of the database are documents and files.

Because PostgreSQL is a traditional relational SQL database, it works well for basic applications where data is structured. For example, an e-commerce front end will work well with a SQL database such as PostgreSQL. Data can be stored using specific data types, and developers can define and categorize data. For an e-commerce store, product descriptions will always be a string of characters, and the price of a product is always a decimal number.

MongoDB vs PostgreSQL

Zeroing in on the right technology to solve a problem can be a nerve-wracking experience. Databases in particular can be challenging to settle on, especially if you’re unclear about how your data will be used. The current data engineering solutions that companies require for data and query processing demand a high learning curve that lacks in PostgreSQL. Although PostgreSQL is easy to deploy on multiple platforms, it does not have the same efficiency on every platform.

The important thing to note here is that transactions allow various changes to a database to either be made or rolled back in a group. Therefore, in a relational database, the data would be modeled across independent parent-child tables in a tabular schema. PostgreSQL uses joins to combine data from multiple tables into a single table. As long as you have 2 tables, you can use joins to combine them in PostgreSQL. Similar to traditional SQL, there are 4 types of joins in PostgreSQL- Inner, Left, Right, and Full Join. If you want all the data from both tables into a single table, you can use a Full Join.

Further, the database is in trend, and most of the IT companies are working using MongoDB as backend technology. We are also offering MongoDB development services in India and the USA. Some specific functions and procedures that do not execute using either MySQL or Mongo DB are possible with PostgreSQL.

Important terms to know before making a database decision

These predictions could be used in front-end reporting for sales and marketing to determine the products that will sell the best in coming years and the most effective price structure. PostgreSQL, also known as Postgres, is an open-source relational database management system that emphasizes extensibility and SQL compliance. Let’s look at the key features on Postgres to get a better sense of its uses. Learn the fundamentals of relational databases and SQL without scrubbing through videos or documentation. Educative’s text-based courses are easy to skim and feature live coding environments.

  • MongoDB’s document data model maps naturally to objects in application code, making it simple for developers to learn and use.
  • However, firstly we should understand each of the databases individually and afterward, will summarize their differences.
  • The language query is simply the best and it has secondary indexes.
  • On the other hand, the data structure of MongoDB doesn’t need to be planned out in advance as it essentially deals with unstructured data.
  • They also have many features that distinguish them from one another.

This article aims to assist you in choosing the right type of database. One of the things that we may struggle with as developers when working on a green field project is our stack. Choosing the right tech to solve a problem can be a harrowing experience. Databases in particular can be a bit tough if we’re unsure how our data is going to be used.

PostgreSQL Is an Object Relational Database

Indexing strategies include B-tree, multicolumn, expressions, and partial, as well as advanced indexing techniques such as GiST, SP-Gist, KNN Gist, GIN, BRIN, covering indexes, and bloom filters. Query performance in MongoDB can be accelerated by creating indexes on fields in documents and subdocuments. MongoDB allows any field of a document, including those deeply nested in arrays and subdocuments, to be indexed and efficiently queried. The strength of SQL is its powerful and widely known query language, with a large ecosystem of tools. We provide best web & mobile app development service from small to large scale businesses. Our efficient development process help you to only focus on result instead of process overhead.

Foreign Key Support

It is likely that you can easily find help to make your SQL database project in general and PostgreSQL project in particular work. There are also a multitude of deployment options for PostgreSQL. PostgreSQL, like Linux, is an example of a well-managed open source project. One of the most broadly adopted relational databases, PostgreSQL came out of the POSTGRES project at the University of California at Berkeley starting in 1986 and it has evolved with the times. But if you have many incumbent applications based on relational data models and teams seasoned just in SQL, a document database like MongoDB may not be a good fit.

Since version 5.0, MongoDB has included a “live” resharding feature that comes as a major time-saver since you only need to set a policy. The database can automatically redistribute the data when the time comes. MongoDB also makes it easy to collaborate between developers or teams, therefore, there’s no need for intermediation or complicated communication between teams.

At the center of the MongoDB platform ecosystem is the database, but it has many layers that provide additional value and solve problems. So use cases that require super speedy queries and massive amounts of data or both can be handled by making ever bigger clusters of small machines. The document model also has emergent properties that make development and collaboration much easier and faster. Below are a few examples of SQL statements and how they map to MongoDB. A more comprehensive list of statements can be found in the MongoDB documentation.


BigAnimal lets you run Oracle SQL queries in the cloud via EDB Postgres Advanced Server. BigAnimal features Oracle compatibility, built-in high availability, and 24/7 support from our team of PostgreSQL experts. If anything changes over the lifetime of the database, then MongoDB requires significant recoding, while Postgres requires more modest changes. In theory, one can use an embedded representation in Postgres, and the Postgres jsonb datatype allows this. However, we have very rarely seen this in practice because of the drawbacks noted above. Instead, one typically uses the representation in Table 1, which corresponds to the “reference” case in MongoDB.

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