---
title: "The 10 Skills I Was Missing as a MongoDB User"
description: "Transitioning from relational databases to MongoDB often leads developers to replicate SQL habits, causing severe performance bottlenecks, brittle schemas, and operational challenges. Effective document design requires balancing referencing and embedding based on query access patterns and update frequencies, rather than placing every entity into separate collections or excessively nesting large documents. Database performance depends on matching indexes to specific query shapes and field orders, which developers can systematically verify by inspecting execution plans using explain plans. Utilizing the built-in aggregation framework allows filtering, grouping, and calculations to run natively inside the database, eliminating slow, manual data transformations in application code. Establishing early monitoring for latency, replication lag, memory usage, and cluster failover resilience ensures stability before adopting advanced tools like Atlas Search and Vector Search."
---

# The 10 Skills I Was Missing as a MongoDB User

[MongoDB](https://yomu.fyi/company/mongodb) · Joel Lord · Oct 2, 2025

**Type:** Explainer

## Summary

Transitioning from relational databases to MongoDB often leads developers to replicate SQL habits, causing severe performance bottlenecks, brittle schemas, and operational challenges. Effective document design requires balancing referencing and embedding based on query access patterns and update frequencies, rather than placing every entity into separate collections or excessively nesting large documents. Database performance depends on matching indexes to specific query shapes and field orders, which developers can systematically verify by inspecting execution plans using explain plans. Utilizing the built-in aggregation framework allows filtering, grouping, and calculations to run natively inside the database, eliminating slow, manual data transformations in application code. Establishing early monitoring for latency, replication lag, memory usage, and cluster failover resilience ensures stability before adopting advanced tools like Atlas Search and Vector Search.

## Context

Applying relational database habits to MongoDB, such as over-normalizing schemas or later over-embedding documents, creates slow queries, data consistency issues, and operational strain.

## Approach / What changed

The author refined MongoDB usage by balancing embedding and referencing via patterns like Extended References, analyzing queries using explain plans, leveraging the aggregation framework for transformations, and monitoring metrics like replication lag and failover behavior.

## Takeaways

- Over-normalizing into separate collections causes slow multi-query stitching, while blindly embedding all data causes oversized documents and slow updates.
- Indexes only improve performance when they match specific query shapes and field orders, which should be verified using explain plans.
- Moving data filtering, grouping, and calculation from application code into MongoDB aggregation pipelines improves query speed and code simplicity.

**Tags:** [Architecture](https://yomu.fyi/topic/architecture), [Monitoring](https://yomu.fyi/topic/monitoring), [Performance](https://yomu.fyi/topic/performance), [Reliability](https://yomu.fyi/topic/reliability)

- Source: [MongoDB](https://www.mongodb.com/company/blog/technical/10-skills-was-missing-as-mongodb-user)
- Source URL: https://www.mongodb.com/company/blog/technical/10-skills-was-missing-as-mongodb-user
- Ingested by Yomu: 2026-08-27T15:04:00.931Z

[Read original post](https://www.mongodb.com/company/blog/technical/10-skills-was-missing-as-mongodb-user)