For enterprise organizations switching to an open source database, understanding the benefits and weaknesses of that database is key. In this blog, we compare PostgreSQL vs. MongoDB — two of the most popular open source databases in use today.
PostgreSQL and MongoDB have a number of similarities, despite being fundamentally different in the way they approach data.
The chart below shows a high-level PostgreSQL vs. MongoDB feature comparison.
In the sections below, we take a closer look at specific areas, including data types, performance, scalability, consistency, availability, and security.
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In our Decision Maker's Guide to Open Source Databases, we provide battlecards for the top open source databases available today -- including insights from our database experts.
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PostgreSQL has a numerous selection of data types which include Boolean, Character, Numeric, Temporal, UUID, Array, JSON, key-value pairs, and special types such as network address and geospatial data.
MongoDB has a rich set of data types which include String, Numeric, Boolean, Min/Max keys, Arrays, Timestamps, Object, Null, Symbol, Date, Object ID, Binary, Code, and Regular Expression. In comparison, the maximum BSON document size is 16 megabytes in MongoDB, and in PostgreSQL the maximum row size is 1.6 terabytes.
Various benchmarks have shown that PostgreSQL outperforms MongoDB for data warehousing and data analysis workloads. But in comparing JSON operations between PostgreSQL and MongoDB, there are benchmarks that show an advantage for both databases. For those with long-term data storage needs, MongoDB performs well with online applications that have very large data stores where data is required to be kept for years.
Scaling is inherently built into MongoDB, but with PostgreSQL an extension is required to add that capability. There are numerous extensions to choose from to achieve scalability with PostgreSQL. You can have as many nodes as needed in a sharded cluster with MongoDB, and PostgreSQL has no limit on database size.
MongoDB shines as a consistency and partition tolerant document store while PostgreSQL focuses on consistency and availability. MongoDB has a single master in a replica set that can accept reads and writes, and the secondaries can be configured for reading. PostgreSQL has a similar setup with a single master, and passive nodes can be configured for reading.
MongoDB and PostgreSQL both support role-based access control functionality as well as popular authentication mechanisms such as LDAP and Kerberos.
Unfortunately, LDAP and Kerberos are a MongoDB enterprise feature. Encrypting connections with industry standard TLS is supported in both products. There are a few different options for encryption at rest with PostgreSQL, but encryption at rest is an enterprise feature with MongoDB.
PostgreSQL has been around 24 years, and it is a solid robust enterprise grade ready relational database with a vibrant development community. If you already have a data model that is not going to change much, then PostgreSQL would be the best option.
Migrating to a NoSQL document database can be a challenge if you have a large data model. Take inventory of your software to check if you have business intelligence analysis and reporting tools as they may depend on a SQL database and will not be able to take advantage of a NoSQL database.
How Agile do you want to be? Creating relational data models take time where a document database such as MongoDB can be more fluid and works well with developers.
If built-in scalability is desired, then MongoDB inherently can scale horizontally with native sharding. Scaling out by adding new nodes or shards can be configured with ease. Automatic failover and replication are also built into MongoDB where PostgreSQL requires either an extension or more configuration to support those features.
Finding the right database largely comes down to the needs of your system and organization. If scaling is a chief requirement, then a database like MongoDB is a good option. If you need more consistent data, PostgreSQL will be worth considering.
Regardless of the database you choose, partnering with a third party for support and guidance is a must.
From PostgreSQL to MongoDB, OpenLogic offers technical support that can get help you meet your goals. Learn more about the databases we support and how we do it.
Enterprise Architect, OpenLogic by Perforce
Bill has over 25 years of experience working in various software roles related to full stack development including user interface, middleware, databases (RDBMS and NoSQL), security, DevOps, training, and mentorship. His primary focus is applying open source in the enterprise.