Mongo DBStudy Notes

Aggregation Performance

Learn practical techniques for diagnosing and improving the performance of MongoDB aggregation pipelines, from index usage to explain plans.

BSON vs JSON

How BSON, MongoDB's binary storage format, differs from JSON in type support, size, and parsing performance.

Common Aggregation Stages

A practical tour of the most frequently used aggregation stages — $match, $project, $sort, $limit, $skip, and $unwind — and how they reshape documents.

Compound Indexes

Understand how MongoDB compound indexes combine multiple fields, the ESR rule for ordering keys, and how they support sorting and covered queries.

Data Modeling Patterns

A tour of named MongoDB schema design patterns — attribute, bucket, computed, subset, and extended reference — and the problems each one solves.

Deleting Documents

Learn how to remove documents from MongoDB collections with deleteOne and deleteMany, and how to safely drop entire collections.

Documents and Collections

How MongoDB structures data into documents and collections, including field types, embedding versus referencing, and the _id field.

Embedding vs Referencing

Understand the core MongoDB modeling trade-off between embedding related data inside a document and referencing it via a separate collection.

Grouping and Accumulators

Master the $group stage and its accumulator operators to compute sums, averages, counts, and other summaries across groups of documents.

Indexes in MongoDB

Learn how MongoDB indexes work internally, why they speed up queries, and how to create and manage the core index types.

Inserting Documents

Learn how to add data to MongoDB collections with insertOne and insertMany, how _id is generated, and how schema flexibility affects inserts.

Installing and Connecting to MongoDB

How to install MongoDB locally or run it with Docker, connect using a connection string, and get started with MongoDB Atlas.

$lookup and Joins in MongoDB

Understand how $lookup performs left outer joins across collections in the aggregation pipeline, from simple equality joins to correlated subqueries.

MongoDB Interview Questions

A curated set of commonly asked MongoDB interview questions and concepts, covering data modeling, indexing, replication, and sharding fundamentals.

MongoDB Quick Reference

A fast lookup guide to the most commonly used MongoDB shell commands, operators, and CRUD syntax for day-to-day development.

Performance Tuning Basics

Practical techniques for diagnosing and fixing slow MongoDB queries, covering the profiler, index hygiene, schema design, and working-set memory.

Query Operators

Master MongoDB's comparison, logical, element, and array query operators like $gt, $in, $and, $exists, and $elemMatch for precise filtering.

Querying Documents

Learn how to retrieve documents from MongoDB collections using find() and findOne(), filters, projections, and cursor methods.

Replica Sets Explained

How MongoDB replica sets provide high availability through automatic failover, elections, and data redundancy across primary and secondary nodes.

Schema Design in MongoDB

Learn how to design MongoDB document schemas around your application's access patterns rather than around abstract normalized tables.

Sharding in MongoDB

How MongoDB distributes data across multiple shards using shard keys, chunks, and a query router to scale horizontally beyond a single server's capacity.

Text and Geospatial Indexes

Learn how MongoDB's text indexes power keyword search and how 2dsphere geospatial indexes enable location-based queries.

The Aggregation Pipeline

Learn how MongoDB's aggregation pipeline transforms documents through an ordered sequence of stages to filter, reshape, and summarize data.

The Mongo Shell and mongosh

How to use mongosh, MongoDB's modern JavaScript-based shell, for interactive queries, scripting, and administration.