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MongoDB vs PostgreSQL Top 8 Most Valuable Comparisons To Learn


Before adding the data, the database schema must be built to get a clear understanding of the data relationships to process the queries. Related information can be stored in separate tables in the database. Relationships between multiple tables of your database add more value to analysis and storage capabilities. Indexes are a type of data structure that can store a very small amount of data in an easily readable form. They are only one component of a join and make your data simple to understand and, thereby help you to resolve any queries with ease.

  • PostgreSQL uses FDW to retrieve the data from other systems as it can change into any form of a data source.
  • PostgreSQL’s design principles place a heavy focus on SQL and relational tables, and allow considerable extensibility.
  • You might be able to alter a table later on, but this may lead to database downtime and bugs in your application.
  • This post isn’t about picking one or either apart — our aim is to help you get a firm grasp of each database’s character and understand which use cases both databases serve best.

Postgres employs SQL ultimately under the hood, a structured query language, to define, to access and to manipulate the database. Postgres does use its own flavor of SQL called PL/pgSQL (procedural language/postgreSQL). The big difference between the two is that the latter can perform more complex queries than SQL. Other relational database models have their own flavor of SQL, which leads to minor differences across the board between the different databases. There are other benefits of using when choosing between MongoDB vs. PostgreSQL.

Architecture/Document Model

Additionally, MongoDB has client-side and field-level encryption, which enables users to encrypt data before sending it to the database via the network. However, as data is stored in key-value pairs in one record, it lacks the security boasted by PostgreSQL; MongoDB’s main focus remains on speed. 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.

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. The main differences between MongoDB vs. PostgreSQL have to do with their systems, architecture, and syntax. Monolithic architecture, meaning that the components are completely united. 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.

MongoDB and PostgreSQL Database Technologies

PostgreSQL databases can use foreign keys which explicitly link data between tables and are used to keep the data normalized. Additionally, as there’s no support for joins, MongoDB databases are oversupplied with data — sometimes duplicate — hence heavily burdening the memory. Distributed architecture, meaning that components function across multiple platforms in collaboration with one another. This also means that MongoDB has nearly unlimited scalability since it can be scaled across more than one platform as needed.

Perform ETL to PostgreSQL vs. MongoDB with

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. With BSON implementation, objects and arrays can be embedded within other objects and arrays. Users are provided a combined advantage of flexible JSON documents along with a high speed lightweight binary format. Both MongoDB and PostgreSQL are really great tools for certain use cases.

MongoDB offers both community support, tutorials, and, for a price, full training and upgrading under the supervision of a support engineer. Because PostgreSQL is widely used, you can be pretty sure that most development tools and other systems have been tested with it and are compatible. PostgreSQL offers many ways to improve the efficiency of the database, but at its core it uses a scale-up strategy. MongoDB Enterprise is based on MongoDB Community edition with additional features that are only available through the MongoDB Enterprise Advanced subscription. Enterprise Advanced includes comprehensive support for your MongoDB deployment. It also adds enterprise-focused features such as LDAP and Kerberos support, on-disk encryption, auditing, and operational tooling.

Developers increasingly pair MongoDB with PostgreSQL, survey finds – TechRepublic

Developers increasingly pair MongoDB with PostgreSQL, survey finds.

Posted: Tue, 03 Nov 2020 08:00:00 GMT [source]

As well as its mature query planner and optimizer, PostgreSQL provides such performance optimizations as table partitioning, read query parallelization, and JIT expression compilations. With reading, you can scale-out PostgreSQL if you create replicas — though each one has to have a complete copy of the database. As you can see from the above MongoDB vs PostgreSQL comparison, both databases have lots to recommend them. This is a terrific option postgresql has many modern features including if your concerns include exploring the limits of SQL, serving up a huge number of queries from many tables, and compatibility. This post isn’t about picking one or either apart — our aim is to help you get a firm grasp of each database’s character and understand which use cases both databases serve best. The translation of SQL to MongoDB queries may take additional time to use the engine which could delay the deployment and development.

PostgreSQL Clause

Both databases support syntax that is quite different from one another. MongoDB, a NoSQL database, stores data in documents and allows users to access it with MQL. PostgreSQL, on the other hand, stores and accesses data using an RDBMS structure and SQL. On top of this, MongoDB offers support for various programming languages. Idiomatic drivers are available for more than a dozen languages, but the MongoDB community has contributed plenty of others. You can take advantage of real-time aggregation, ad-hoc queries, and rich indexing to give powerful programmatic ways to access and examine data of all structure types.

MongoDB and PostgreSQL Database Technologies

Using a drag-and-drop-based interface, permits users with zero coding experience to build data pipelines and effectively clean and transfer high-volume data sets. This entire process doesn’t require complicated code, so you can move data to the database of your choice without any data engineering experience. Choose from data integration methods such as ETL, ELT, ReverseETL, CDC, and more. They help you to resolve queries with greater efficiency by making the data simpler and thereby easier to scan. Both databases use different syntax and terminology to perform many of the same tasks.

Which Database Is Right For You? HarperDB vs. MongoDB vs. PostgreSQL

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. MongoDB is a non-relational database, while PostgreSQL is a relational database. While NoSQL databases work on storing data in key-value pairs as one record, relational databases store data on different tables. Furthermore, you can also review various groups or users’ data access activities with the auditing option which grants an extra layer of security.

In the competitive field of Data Analytics, having a majority customer share in the market and offering efficient products and services helps determine the company’s profit. When it comes to Database Management, the choice between MongoDB and PostgreSQL is pretty difficult. This strength is due to the database’s stable progress over the years. One of the most impressive details about PostgreSQL is that it offers support for all transaction isolation levels specified in the SQL standard, along with serializable. PostgreSQL’s design principles place a heavy focus on SQL and relational tables, and allow considerable extensibility.

MongoDB and PostgreSQL Database Technologies

Image SourceMongoDB also offers an On-Premise pricing model with MongoDB Enterprise Advanced edition. This way, PostgreSQL can update both records at the same time, thus reducing the number of errors and maintaining a complete and accurate backup as well. It is open-source and so any user can use all of its features, free of cost. comes with out-of-the-box connectors for both MongoDB vs. PostgreSQL, helping you move data to the database of your choice without breaking a sweat.

PostgreSQL’s ideal purpose

PostgreSQL defaults to the read committed isolation level, enabling users to adjust it to the serializable isolation level. If you’re starting a development project and want to understand your needs and data model through an agile development process, MongoDB should work wonders. Developers have the flexibility to reshape data independently as required. You can also manage data of any structure — not just tabular ones you define ahead of time.

The syntax supported by both databases is quite different from each other. MongoDB, being a NoSQL database, leverages documents to store data, allowing users to access it using MQL. PostgreSQL on the other hand uses an RDBMS structure and SQL to store and access data respectively. While MongoDB does not support FOREIGN KEY constraints, PostgreSQL does. A foreign key can be one column or a group of columns that you can use to create a link in data from multiple tables at the same time. MongoDB aggregation pipelines are made up of multiple stages to transform data.

MongoDB adds elements to the document model and the query engine to handle both geospatial and time series tagging of data. This expands the type of queries and analytics that can be performed on a database. MongoDB generally stores the data like documents and represented in a binary form which is called binary JSON.

PostgreSQL is getting popularity because of its structure and wide range of use. The developers are available for this technology more in number rather than for MongoDB. MongoDB is also getting popular as it getting used with new technologies like ReactJS etc. Similarly, each user information would include details such as name, address, permissions and user ID.

Overview of MongoDB and PostgreSQL

Known as Postgres, these are Object Relational Database Management System . The emphasis of this is on extensibility and yardsticks compliance. PostgreSQL is available for a number of platforms including FreeBSD, Linux, Micrsoft Windows, Mac OS X.

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. MongoDB is especially capable of handling data structures that have been created by modern apps and APIs. It’s perfectly positioned to offer support for the agile, ever-changing development cycle seen in organizations today. Thanks to the document model’s emergent properties, development and collaboration are both simpler and quicker. From a programmer’s point of view, MongoDB transactions resemble those that developers will be familiar with from PostgreSQL.

For reads, it is possible to scale-out PostgreSQL by creating replicas, but each replica must contain a full copy of the database. 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 strength of SQL is its powerful and widely known query language, with a large ecosystem of tools. This flexibility is hugely useful when consolidating information from diverse sources or accommodating variations in documents over time, especially as new application functionality is continuously deployed. Now, the intriguing fact is the higher rank of PostgreSQL compared to MongoDB among most popular database systems in 2020.

PostgreSQL, on the other hand, is a free, open-source RDBMS that was developed at the University of California, Berkley. Both these technologies are leveraged by organizations of all scales, both big & small, and depending on the situation, one can dominate over the other. Like MySQL and other open source relational databases, PostgreSQL has been proven in the cauldron of demanding use cases across many industries. MongoDB is based on a distributed architecture that allows users to scale out across many instances, and is proven to power huge applications, whether measured by users or data sizes.