There is No "Best" Database
Students often ask, "Is MongoDB better than Postgres?" The real answer depends on where you stand on the CAP triangle.
1. CP (Consistency + Partition Tolerance)
Goal: The data must be correct, even if the system has to shut down to ensure it.
- When to choose: Banking systems, ATM transactions, and stock trading. You’d rather the ATM say "Service Unavailable" than give out money you don't actually have in your account.
- Examples: Redis, MongoDB (in certain configs), HBase.
2. AP (Availability + Partition Tolerance)
Goal: The system must stay online, even if some users see slightly "old" data for a few seconds.
- When to choose: Social media feeds, YouTube comments, or "Likes" on a post. If I see 99 likes and you see 100, the world won't end. But if the "Like" button stops working entirely, that's a bad user experience.
- Examples: Cassandra, DynamoDB, CouchDB.
3. CA (Consistency + Availability)
Goal: Perfect data and 100% uptime.
- The Reality: This only works if your network never fails. Since network partitions are inevitable in distributed systems, CA is basically impossible for a truly distributed system. It usually refers to single-node databases like a standard MySQL setup.
[Image comparing CP vs AP systems with real-world application examples]
Final Verdict
- Pick CP when the accuracy of data is the primary value.
- Pick AP when the uptime of the system is the primary value.
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