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  • Why PostgreSQL is Strongly Consistent and MongoDB is . . .
    In distributed system design, trade-offs are inevitable The key is to understand them clearly and use the right tools for the right context PostgreSQL gives you consistency by default MongoDB
  • How MongoDB Loses Availability in the CAP Theorem - Medium
    MongoDB’s trade-off between Consistency and Availability is ideal for applications where data consistency is more important than total uptime Here’s a summary to guide you:
  • CAP Theorem - MongoDB (NoSQL) : WWW. DBVERSITY. COM
    In the context of NoSQL databases like MongoDB, different databases may make different trade-offs based on their design principles and intended use cases Some NoSQL databases prioritize consistency and partition tolerance (CP), while others prioritize availability and partition tolerance (AP)
  • mongodb - How does Mongos eventual consistency work with a . . .
    In general here is what happens when you do a write (simplified) with journaling enabled: The operation is checked for being syntactically correct The query optimizer kicks in and does his stuff (Irrelevant for this question, so I spare the details) The write operation is applied to the in memory representation of the data set called
  • Composite Thrashing Code Adrons success in misadventures of . . .
    The CAP theorem emphasizes the trade-offs between Consistency, Availability, and Partition Tolerance in distributed systems like MongoDB Prioritizing Availability and Partition Tolerance, MongoDB uses replica sets and sharding for resilience while allowing configurable consistency
  • Where do MongoDB Stand on Cap Theorem? - Scaler
    The Mongodb CAP theorem highlights the trade-offs involved in designing distributed systems, and MongoDB's design prioritizes availability and partition tolerance while allowing flexibility in choosing the desired level of consistency
  • Read Isolation, Consistency, and Recency - MongoDB
    Without isolating the multi-document write operations, MongoDB exhibits the following behavior: Non-point-in-time read operations Suppose a read operation begins at time t 1 and starts reading documents A write operation then commits an update to one of the documents at some later time t 2


















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