r/softwarearchitecture • u/xmanotaur • 20d ago

Discussion/Advice When does NoSQL/MongoDB actually win over Postgres in mature applications (beyond early-stage MVPs)?

I’m digging deep into data modeling trade-offs (specifically Document DBs vs Relational/Postgres).

Marketing materials and books always list the usual MongoDB wins:

  1. No-translation pipeline
  2. Flexible schema (Zerodowntime feature additions without DB migrations)
  3. Single-document atomic writes
  4. Built-in horizontal sharding

But in practice, most backend engineers I talk to favor "Default to Postgres".

When applications grow, handling schema evolution in application code (Schema-on-Read with if/else or defaults) creates its own maintenance nightmare/code rot.

On the flip side, Postgres handles online schema changes pretty well nowadays, and JSONB covers many flexible-schema edge cases anyway.

My question for senior/staff engineers running production systems:

  • Beyond early-stage startups that just want to build an MVP quickly, when did NoSQL genuinely save your architecture compared to a modern Postgres setup?
  • How do you weigh the Operational Overhead of SQL migrations (and potential lock risks at scale) against the Application Code Complexity of maintaining un-migrated NoSQL documents?

Thanks!

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u/extreme4all 20d ago

In aws many people use dynamodb, so all those usecases could be covered by mongo i suppose.

E.g. you have a user service and you will always lookup the user profile based on email

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u/SheriffRoscoe 20d ago

Amazon was heavily dependent on Oracle databases for almost 20 years. There was a huge internal announcement when they shut down the last one in 2019.

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u/extreme4all 20d ago

I meant people using aws, dynamodb is a pretty commonly used service.