Mongodb

Use MongoDB when your data is hierarchical/nested (e.g., product catalogs with varying attributes, user profiles with embedded arrays), your schema evolves frequently without costly migrations, or you need horizontal sharding from the start. Use PostgreSQL when you have complex relational data with joins, need strong ACID guarantees across multiple tables, use complex SQL queries (window functions, CTEs), or want a battle-tested relational database with the richest feature set. Many teams use both: PostgreSQL for transactional data, MongoDB for flexible document storage.

MongoDB Atlas offers a permanently free M0 cluster with 512MB storage, shared CPU, and RAM across AWS, Azure, or GCP regions. This is sufficient for learning, development, and small hobby projects. Paid tiers start at M2 ($9/month, 2GB) and M5 ($25/month, 5GB). Production workloads typically use M10+ ($57/month, 2GB dedicated RAM). Serverless Atlas pricing is usage-based: $0.10/million reads, $1.00/million writes. The free tier has no time limit.

MongoDB is very beginner-friendly for developers coming from JavaScript/JSON backgrounds — documents map directly to JS objects, making the mental model intuitive. The Atlas free tier removes infrastructure management. MongoDB University offers free courses and certifications. The main learning curve is understanding when NOT to use MongoDB — for relational data with complex joins, it forces awkward workarounds. Beginners should learn both MongoDB and PostgreSQL to understand the trade-offs.