MongoDB’s document data model maps naturally to objects in application code, making it simple for developers to learn and use. MongoDB: The Scalable Document Database That Has Become a Data Platform So, now that the impatient have been satisfied, the patient can take a deeper dive into MongoDB, then PostgreSQL, and then a comparison. If you are a creative SQL developer and want to push SQL to the limits by using advanced techniques for indexing, storing and searching numerous structured data types, creating user-defined functions in a variety of languages, and tuning the database to the nth degree, you likely will be able to go further with PostgreSQL than any other RDBMS. If you want a relational database that will run complex SQL queries and work with lots of existing applications based on a tabular, relational data model, PostgreSQL will do the job. If you are a SQL shop and introducing a new paradigm will cost more than any other benefits mentioned will offset, PostgreSQL is a choice that will likely meet all your needs. If you want a multi-cloud database that works the same way in every public cloud, can store customer data in specific geographic regions, and support the latest serverless and mobile development paradigms, MongoDB Atlas is the right choice. If you are supporting an application you know will have to scale in terms of volume of traffic or size of data (or both) and that needs to be distributed across regions for data locality or data sovereignty, MongoDB’s scale-out architecture will meet those needs automatically. MongoDB enables you to manage data of any structure, not just tabular structures defined in advance. If you are at the beginning of a development project and are seeking to figure out your needs and data model by using an agile development process, MongoDB will shine because developers can reshape the data on their own, when they need to. The rest of this article aims to provide information that helps make a safe bet.īut again, for those who want the story right away, here is a summary of our general guidance: They have to make a bet about the best fit. 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.īut often at the beginning of a development project, the project leaders often have a good grasp of the use case, but don’t really have clarity about the specific application features their business and users will need. The right answer for your needs is based of course on what you are trying to do. If a SQL database fits your needs, then Postgres is a great choice. If you are looking for a distributed database for modern transactional and analytical applications that are working with rapidly changing, multi-structured data, then MongoDB is the way to go. If your concerns are compatibility, serving up thousands of queries from hundreds of tables, taking advantage of existing SQL skills, and pushing SQL to the limit, PostgreSQL will do an awesome job.īoth Databases Are Awesome, But What Is Your Need?Īs an astute reader should already be able to tell, the real question is not MongoDB vs Postgres, but the best document database versus the best relational database. Everything you would ever want from a relational database is present in PostgreSQL, which relies on a scale-up architecture. PostgreSQL is a rock solid, open source, enterprise-grade SQL database that has been expanding its capabilities for 30 years. If your concerns are time to market, developer productivity, supporting DevOps and agile methodologies, and building stuff that scales without operational gymnastics, MongoDB is the way to go. MongoDB handles transactional, operational, and analytical workloads at scale. It is built on a distributed, scale-out architecture and has become a comprehensive cloud-based platform for managing and delivering data to applications. MongoDB is the leading document database. MongoDB vs PostgreSQL: A Comparison in Briefįor those of you who want the news right up front, here it is in 135 words.

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