Why did PostgreSQL 17 outperform MongoDB 8.0 in analytical benchmarks?

In tests involving one million rows, PostgreSQL 17 handled complex analytical aggregations nearly three times faster than MongoDB 8.0. This performance gap is largely due to PostgreSQL’s sophisticated cost-based query planner, which is designed to manage complex relationships and joins with high efficiency. While MongoDB’s aggregation pipelines have improved, they often struggle with operations that span multiple entities because the engine was originally optimized for single-record isolation rather than complex relational stitching.

How do the two databases handle updates to JSON data differently?

The two systems use different storage mechanics that impact performance during write-heavy workloads. PostgreSQL uses Multi-Version Concurrency Control (MVCC), which creates a new version of an entire row even when only a small field within a JSONB document is updated, leading to "write amplification" and increased CPU usage. In contrast, MongoDB’s WiredTiger engine can often modify specific fields within a BSON document without rewriting the entire record, resulting in steadier throughput and more predictable latency during sustained update stress tests.

What is the "hybrid model" recommended for modern web applications?

The hybrid model involves using PostgreSQL to store core entities in strict relational columns while using the JSONB data type for flexible metadata or variable attributes. This approach allows developers to benefit from relational integrity and ACID transactions for critical data, like user IDs and emails, while maintaining the "escape hatch" of document flexibility for parts of the data that may change frequently. This strategy was highlighted as a way to avoid "schema regret," where a purely flexible database becomes a disorganized collection of inconsistent records.

When is MongoDB a better choice than PostgreSQL for scaling?

MongoDB is considered a "horizontal scaling specialist" because it was built with native sharding as a core feature, making it easier to distribute data across multiple machines or geographic regions. This makes it a superior choice for apps dealing with hundreds of terabytes of data or high-volume IoT telemetry. While PostgreSQL can scale vertically with more RAM and faster drives, or horizontally through specific extensions and managed services, MongoDB’s built-in ability to handle massive write-heavy volumes across clusters remains its primary architectural advantage.

PostgreSQL vs MongoDB: Which is better for web apps?

22 min

Choosing a database shouldn't be based on vibes. We compare speed and JSONB flexibility to help you pick the right engine for your next application.

PostgreSQL vs MongoDB: Which is better for web apps?

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How Postgres and Mongo DB differ and how they are the same. What solution is better for web apps?

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"Reading used to feel like a chore. Now it’s just part of my lifestyle."

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"Feels effortless compared to reading. I’ve finished 6 books this month already."

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"BeFreed turned my commute into learning time. 20-min podcasts are perfect for finishing books I never had time for."

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