CouchDB vs MongoDB

CouchDB

Document database with HTTP API and multi-master sync

MongoDB

Document-oriented NoSQL database for flexible schemas

Feature CouchDB MongoDB
Category Databases Databases
Sub-category Document Document
Maturity mature mature
Complexity beginner beginner
Performance tier medium medium
License Apache-2.0 SSPL
License type permissive source-available
Pricing fully free fully free
GitHub stars 6.0K 27.0K
Contributors 200 1.0K
Commit frequency weekly weekly
Plugin ecosystem none none
Docs quality good good
Backing org Apache Foundation MongoDB Inc
Funding model foundation open_core
Min RAM 512 MB 512 MB
Min CPU cores 1 2
Scaling pattern horizontal horizontal
Self-hostable Yes Yes
K8s native No No
Offline capable Yes Yes
Vendor lock-in none none
Languages Erlang C++
API type REST REST
Protocols HTTP HTTP
Deployment docker, apt, binary docker, apt, binary
SDK languages
Team size fit solo, small, medium, enterprise solo, small, medium, enterprise
First release 2020 2020
Latest version

When to use CouchDB

  • Primary: offline-first-apps
  • Primary: mobile-data-sync
  • Primary: distributed-web-apps

When to use MongoDB

  • Primary use: content-management
  • Primary use: catalog-storage
  • Primary use: real-time-analytics

CouchDB anti-patterns

  • Limited query capabilities vs MongoDB
  • MapReduce can be slow
  • Smaller ecosystem than MongoDB

MongoDB anti-patterns

Full CouchDB profile → Full MongoDB profile → All comparisons