Key differences, specifications and fit guidance for MongoDB and PostgreSQL, compiled from official documentation and the iThub profiles.
MongoDB is a document database that stores JSON-like documents in collections, with replication, sharding and a managed Atlas service.
PostgreSQL is a free, open source object-relational database that extends SQL, with JSON/JSONB support, MVCC and many index types.
Choose MongoDB if your data maps naturally to nested documents with a flexible schema and you want built-in sharding or the managed Atlas service; choose PostgreSQL if you need a relational model with SQL, strict isolation levels and a permissive open source licence, while still storing JSON in JSONB columns. Both support ACID transactions and replication. The deciding factors are data shape and query style, the licence, since MongoDB Community uses the SSPL and PostgreSQL a BSD-style licence, and whether you want a vendor-run cloud service or a community project.
Choose MongoDB ifShortlist MongoDB when your data is nested and varies between records, embedded documents can replace joins, and you want built-in sharding or a vendor-managed Atlas cluster on AWS, Azure or Google Cloud.
Choose PostgreSQL ifShortlist PostgreSQL when your data is relational, queries depend on SQL and joins, and you want strict isolation levels, rich indexing and a permissive open source licence.
| Aspect | MongoDB | PostgreSQL |
|---|---|---|
| Data model | MongoDB stores JSON-like documents in collections that do not enforce a rigid, pre-defined schema, and embedded documents and arrays reduce the need for joins. | PostgreSQL is an object-relational database that uses and extends SQL, and adds JSON/JSONB, XML and Hstore types for document data inside tables. |
| Schema enforcement | MongoDB uses a flexible schema by default, so documents in a collection need not share fields; optional schema validation rules can restrict data types and value ranges. | PostgreSQL defines structure through tables and data types, and lets users add their own data types and functions when the built-in ones are not enough. |
| Licence model | The MongoDB Community source is published under the Server Side Public License, which requires releasing service source code if you offer the program as a service. | PostgreSQL uses the PostgreSQL License, a liberal open source licence similar to the BSD or MIT licences. |
| Transactions and concurrency | Single-document operations in MongoDB are atomic, and multi-document ACID transactions are available across collections, databases and shards when needed. | PostgreSQL has been ACID compliant since 2001, uses MVCC so reads and writes do not block each other, and supports every SQL standard isolation level. |
| Horizontal scaling | MongoDB uses sharding to distribute data across machines for very large data sets and high throughput, with mongos routing queries to the right shards. | PostgreSQL offers asynchronous, synchronous and logical replication, active standbys and table partitioning on its feature list. |
| Indexing and querying | MongoDB is queried through its MongoDB Query API and supports workloads including aggregation, full-text, vector, geospatial and time series search. | PostgreSQL uses SQL with SQL/JSON functions and JSON_TABLE, and offers GiST, SP-GiST, GIN, BRIN and Bloom indexes, with GIN indexes for searching jsonb keys. |
| Managed service | MongoDB Atlas runs databases on AWS, Azure and Google Cloud and handles provisioning, patching, backup, monitoring and scaling, with a free M0 tier and hourly billing. | PostgreSQL has no vendor-run service from the project; hosting and commercial support come from many independent companies alongside community support. |
| Availability and recovery | MongoDB replication provides automatic failover, data redundancy and increased read capacity, electing a new primary when the current one becomes unavailable. | PostgreSQL provides point-in-time recovery and active standbys alongside its built-in replication options. |
From the iThub profiles. “Not recorded” means the profile does not confirm it. Confirm prices and editions with each vendor.
| Attribute | MongoDB | PostgreSQL |
|---|---|---|
| Starting price | Free edition or plan ↗ | Free edition or plan |
| API | Yes | Yes |
| Founded | 2007 | 1996 |
| Headquarters | New York, USA | Open Source Project |
| GitHub stars | 28.7K ↗ | 22.7K ↗ |
| Documentation | Official docs ↗ | Official docs ↗ |
MongoDBMongoDB is a document database designed to help developers build applications faster. It stores data in flexible, JSON-like documents, so the data model can mirror the objects in application code. A record is a document made of field and value pairs, and field values can include other documents, arrays and arrays of documents.
Documents are stored in collections. Collections are similar to relational tables but do not enforce a rigid, pre-defined schema. MongoDB supports multi-document ACID transactions for operations that need consistency, replication with automatic failover for availability, and sharding for horizontal scaling to large datasets and high throughput.
PostgreSQLPostgreSQL is an open source object-relational database system that uses and extends the SQL language. Its origins date back to 1986 and the POSTGRES project at the University of California at Berkeley, and it has nearly 40 years of active development on the core platform. It is free and open source, and it runs on all major operating systems.
PostgreSQL has been ACID-compliant since 2001. Its feature list includes multi-version concurrency control (MVCC), table partitioning and every transaction isolation level defined in the SQL standard, including Serializable. Indexing options go beyond B-tree to GiST, SP-GiST, GIN, BRIN, covering indexes and Bloom filters.
MongoDB and PostgreSQL take opposite starting points. MongoDB is a document database that stores JSON-like documents in schema-flexible collections, scales out with sharding and is offered as the managed Atlas service. PostgreSQL is a community-run object-relational database built on SQL, with strict isolation, many index types and JSONB for document data, under a BSD-style licence.
Start by mapping your main entities and how often they are read together or updated separately. Decide whether you will run the database yourself or buy a managed service, check licence terms against how you will distribute or host the software, and list the queries that must stay fast as data grows.
Model one real domain, such as orders with line items, in both databases: nested documents in MongoDB and normalised tables plus a JSONB variant in PostgreSQL. Load identical data, run the same read, update and reporting queries, add indexes, test a multi-record transaction and a failover, and compare latency, storage size and code complexity.
Not in the same way. The MongoDB Community source code is published under the Server Side Public License (SSPL), which requires anyone offering the program as a service to release the service source code. PostgreSQL is released under the PostgreSQL License, a liberal open source licence similar to the BSD or MIT licences, with no such service clause.
Often, for many workloads. PostgreSQL stores documents in JSON and JSONB columns, offers SQL/JSON query functions and JSON_TABLE, and GIN indexes can search keys or key/value pairs across many jsonb documents. MongoDB is built around documents, with flexible collections, embedded arrays and the MongoDB Query API, which may suit document-first applications better.
Yes. MongoDB supports multi-document ACID transactions across operations, collections, databases, documents and shards, and operations on a single document are atomic. Its document model encourages embedding related data in one document, which reduces how often multi-document transactions are needed. PostgreSQL has been ACID compliant since 2001 and supports every SQL standard isolation level.
They scale differently. MongoDB has built-in sharding to distribute data across machines for very large data sets and high throughput, with mongos routing queries. PostgreSQL lists asynchronous, synchronous and logical replication, active standbys and table partitioning. Test your own data volume and write rate on both before deciding.
MongoDB Atlas is the vendor's managed service; it runs on AWS, Azure and Google Cloud, handles provisioning, patching, backup and scaling, and offers a free M0 tier with clusters billed hourly. PostgreSQL has no service run by the project itself, but many commercial companies offer PostgreSQL hosting and support.
Choose MongoDB when your records are naturally nested documents whose fields vary between records, when embedding data avoids frequent joins, or when you expect to shard large datasets. Choose PostgreSQL when data is relational, queries rely on SQL and joins, or you need strict isolation levels and a permissive licence.
Facts on this page come from these official pages, checked on , and from the iThub profiles. Vendors change plans and features: confirm with them before buying.
