When comparing MongoDB vs PostgreSQL, the Slant community recommends PostgreSQL for most people. In the question“What are the best databases to use for Node.js applications?” PostgreSQL is ranked 1st while MongoDB is ranked 5th. The most important reason people chose PostgreSQL is:
PostgreSQL performance increases with each release, this is also proven by many benchmark tests. Notable performance features include: * As PostgreSQL only supports one storage engine, it has been able to integrate and optimise it and with the rest of the database. This has resulted in multiple benefits such as the ability to allow different transaction types to co-exist efficiently without the need to select storage engine types once for each table ahead of time. * On the fly data compression resulting in less IO required for reading. * Asynchronous + synchronous Replication. * PostgreSQL supports a asynchronous API for use by client applications. It is reported to increase performance by up to 40% and is not supported by MySQL. * Designed to scale very well with large numbers of cores at high concurrency levels.
Specs
Ranked in these QuestionsQuestion Ranking
Pros
Pro Perfect documentation and tutorials
Miles above other databases in educational resources.
Pro Great speed
MongoDB queries can be very fast because the data is usually all in one place and can easily be retrieved in a single lookup. But this is true only when the data is truly a document. When it's trying to emulate a relational model it starts to become really slow because it may have to perform many independent queries to retrieve a single document.
Pro Uses JSON
As Node.js uses JavaScript there's no need to map the returned JSON data from MongoDB, as JavaScript is a superset of JSON. Essentially solving object-relational impedance mismatch by its very nature. Working with JSON is also easier overall as it more easily fits into how you would represent data on the client.
Pro Doesn't require a unified data structure
Mongo is very flexible in that it doesn't require a unified data structure across all objects. So it's rather easy to use.
Pro Easy to scale
MongoDB has powerful sharding and scaling capabilities for when the data stored in the database gets so large that a single machine may not be able to store all of it. Sharding solves this problem through horizontal scaling. Mongo gives developers the ability to easily and painlessly add or remove as many machines as needed.
Pro High performance
PostgreSQL performance increases with each release, this is also proven by many benchmark tests.
Notable performance features include:
As PostgreSQL only supports one storage engine, it has been able to integrate and optimise it and with the rest of the database. This has resulted in multiple benefits such as the ability to allow different transaction types to co-exist efficiently without the need to select storage engine types once for each table ahead of time.
On the fly data compression resulting in less IO required for reading.
Asynchronous + synchronous Replication.
PostgreSQL supports a asynchronous API for use by client applications. It is reported to increase performance by up to 40% and is not supported by MySQL.
Designed to scale very well with large numbers of cores at high concurrency levels.
Pro Fully ACID compliant
PostgreSQL is known to have a very holistic approach to robustness and data integrity which is reflected by it being fully ACID compliant.
PostgreSQL has always been strict about making sure data is valid before allowing it into the database, and there is no way for a client to bypass those checks.
Depending on your requirements, ACID compliance might be important.
Pro Strong community
PostgreSQL has a strong community backing it, with guides, tutorials and support for any kind of problem a developer may have.
Pro Support for JSON data type
JSON data can be stored as a column with optional indexes. In 9.4 (upcoming at the time of this writing), JSONB will be a binary version of JSON that will save space. It's like the best of the NO-SQL world without having to give up ACID and Relationships. This means that cascading deletes can be done in a single Transaction across multiple JSON documents.
Pro Actively developed
Regular fixes and features are released
Pro Support for geographic objects
PostgreSQL can be extended to have geographic object support through PostGIS and allows for location queries to be run through SQL.
Pro Multiple node packages available
There are many packages (like Sequelize) that integrate deeply with the features Postgres offers.
Pro Support Perl and Python for coding stored procedures
Postgres supports popular languages for coding stored procedures, such as Perl and Python. So, you can fairly easy transform just DB-server to reliable Service with complex business logic.
Pro Open Source, powerful and on par with other paid RDBMS'
It is a powerful, open source product that has all the bells and whistles when compared with its costly, proprietary counterparts.
Cons
Con Reported to lose or corrupt data
MongoDB is famously known for leaking and losing data over time.
Con Document Stores may be not suited for relational data
MongoDB has no JOIN, all relations are supposed to be resolved client-size which entails additional requests to the server.
Con Need many search features
Though it is possible to index and search text in documents in MongoDB 4.0 in multiple languages. The indexing and search is not as powerful as for example Elastic Search. For instance not being able to search for only parts of words.
Con Not suited for small apps
Because of it's complexity and power, it may be an overkill to use PostgreSQL in small applications that will not make use of it's full power.