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Technology 161 Topics

MongoDB Full Tutorial

1
Part 1: Introduction to MongoDB: NoSQL Architecture, Document Model, and BSON Fundamentals
1
Part 1: Introduction to MongoDB: NoSQL Architecture, Document Model, and BSON Fundamentals
2
Part 2: MongoDB vs Relational Databases (RDBMS): ACID, Joins, Schema Flexibility, and Scaling
3
Part 3: Installing MongoDB Community Server and MongoDB Shell (mongosh) on Linux, macOS, and Windows
4
Part 4: The WiredTiger Storage Engine: Cache Architecture, Checkpoints, Journaling, and Compression
5
Part 5: BSON Data Types Deep Dive: ObjectId, Date, Timestamp, Decimal128, and Binary Data
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Part 6: Anatomy of an ObjectId: Timestamp, Machine Identifier, Process ID, and Counter Mechanics
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Part 7: Connecting to MongoDB: Connection Strings, URI Schemes (mongodb:// vs mongodb+srv://), and Options
8
Part 8: Navigating the MongoDB Shell (mongosh): Databases, Collections, and Shell Helpers
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Part 9: System Catalogs and Metadata: system.views, system.profile, and Database Administration Commands
10
Part 10: Managing Collections: Creating, Renaming, Dropping, and Capped Collections
11
Part 11: Capped Collections: Fixed-Size Circular Buffers for High-Throughput Logging and Caching
12
Part 12: Time Series Collections: Optimized Storage and Compression for Sensor and Metric Data
13
Part 13: Clustered Collections: Primary Key Clustered Indexes for Faster Range Lookups
14
Part 14: Database Commands vs Shell Methods: Understanding db.runCommand() and Admin Primitives
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Part 15: MongoDB Configuration File (mongod.conf): Network, Storage, SystemLog, and ProcessManagement
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Part 16: Inserting Documents: insertOne() vs insertMany() vs insert()
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Part 17: Ordered vs Unordered Inserts: Batch Processing, Performance, and Error Handling
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Part 18: Querying Documents: find() and findOne() Mechanics and Cursor Execution
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Part 19: Query Projection: Selecting and Excluding Specific Fields to Reduce Network Payload
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Part 20: Comparison Query Operators: $eq, $ne, $gt, $gte, $lt, $lte, and Value Comparisons
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Part 21: Set Membership Query Operators: $in, $nin and Multi-Value Lookups
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Part 22: Logical Query Operators: $and, $or, $nor, $not and Compound Conditions
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Part 23: Element Query Operators: $exists and $type for Dynamic Schema Verification
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Part 24: Evaluation Query Operators: $regex, $text, $mod, and $expr for Field-to-Field Comparisons
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Part 25: Querying Embedded Documents: Dot Notation, Nested Object Matching, and Subdocuments
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Part 26: Querying Arrays of Primitives: Exact Array Matching vs Element Containment
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Part 27: Array Query Operators: $all, $elemMatch, and $size Mechanics
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Part 28: Querying Arrays of Embedded Documents: Filtering Nested Objects with $elemMatch
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Part 29: Cursors in MongoDB: Cursor Methods (next, hasNext, toArray, forEach) and Cursor Timeouts
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Part 30: Pagination Strategies: Skip-Limit vs Keyset (Range-Based / Seek) Pagination
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Part 31: Updating Documents: updateOne() vs updateMany() vs replaceOne()
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Part 32: Field Update Operators: $set, $unset, $rename, and $setOnInsert
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Part 33: Numeric Field Operators: $inc, $mul, $min, and $max for Atomic In-Place Updates
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Part 34: Date and Timestamp Update Operators: $currentDate for Audit Tracking
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Part 35: Upserts: Conditional Insert-or-Update Operations and Best Practices
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Part 36: Array Update Operators: $push, $addToSet, $pop, and $pull
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Part 37: Advanced Array Modifiers: $each, $slice, $sort, and $position with $push
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Part 38: Positional Array Operator ($): Updating the First Matching Array Element
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Part 39: All Positional Operator ($[]): Updating Every Element Across an Entire Array
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Part 40: Filtered Positional Operator ($[identifier]): Updating Specific Array Elements with arrayFilters
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Part 41: Deleting Documents: deleteOne() vs deleteMany() and Safe Deletion Strategies
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Part 42: Bulk Write Operations: bulkWrite() for High-Throughput Batch Processing
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Part 43: Array Projection Operators: $, $elemMatch, and $slice in Query Projections
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Part 44: The $expr Operator: Comparing Two Fields within the Same Document
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Part 45: Bitwise Query Operators: $bitsAllClear, $bitsAllSet, $bitsAnyClear, $bitsAnySet
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Part 46: Geospatial Fundamentals: GeoJSON Objects (Point, LineString, Polygon, MultiPolygon)
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Part 47: Geospatial Queries: $near, $nearSphere, $geoWithin, and $geoIntersects
48
Part 48: Working with 2dsphere and 2d Indexes for Location-Based Services
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Part 49: Sorting Query Results: sort() Direction, Multi-Field Sorting, and Memory Limits
50
Part 50: Counting Documents: estimatedDocumentCount() vs countDocuments() Performance
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Part 51: Distinct Values: distinct() Query Execution and Memory Overhead
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Part 52: Finding and Modifying in a Single Atomic Operation: findOneAndUpdate()
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Part 53: Atomic Document Replacement: findOneAndReplace() and Options
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Part 54: Atomic Document Deletion: findOneAndDelete() for Task Queue Implementations
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Part 55: Write Conflict Handling and Optimistic Concurrency Control (OCC) in MongoDB
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Part 56: How Indexes Work in MongoDB: B-Tree Data Structures and Index Entries
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Part 57: Single Field Indexes: Creation, Ascending vs Descending, and Default _id Index
58
Part 58: Compound Indexes: Field Ordering, Equality-Sort-Range (ESR) Rule, and Index Prefixes
59
Part 59: Multikey Indexes: Indexing Arrays, Index Limitations, and Space Overhead
60
Part 60: Unique Indexes: Enforcing Business Uniqueness, Missing Fields, and Duplicate Keys
61
Part 61: Partial Indexes: Indexing Subsets of Documents to Conserve Memory and Disk
62
Part 62: Sparse Indexes: Indexing Documents Containing the Target Field vs Partial Indexes
63
Part 63: Time-To-Live (TTL) Indexes: Automatic Document Expiration for Sessions and Logs
64
Part 64: Text Indexes: Full-Text Search, Stemming, Stop Words, and Text Score Weights
65
Part 65: Wildcard Indexes: Indexing Dynamic, Unpredictable, or Highly Arbitrary Attributes
66
Part 66: Covered Queries: Satisfying Queries Entirely from RAM Without Fetching Documents
67
Part 67: Analyzing Queries with explain(): executionStats, queryPlanner, and allPlansExecution
68
Part 68: Interpreting Explain Output: COLLSCAN vs IXSCAN, docsExamined vs nReturned
69
Part 69: Index Cardinality, Selectivity, and Hidden Indexes for Zero-Downtime Migration
70
Part 70: Index Maintenance: createIndex(), dropIndex(), listIndexes(), and Storage Profiling
71
Part 71: Introduction to the Aggregation Pipeline: Concepts, Stages, and Architecture
72
Part 72: Filtering and Reshaping: $match and $project Stages
73
Part 73: Grouping and Aggregation: The $group Stage and Accumulator Operators ($sum, $avg, $max, $min)
74
Part 74: Advanced Accumulators: $addToSet, $push, $first, $last, and $accumulator
75
Part 75: Sorting and Limiting in Pipelines: $sort, $limit, and $skip Stage Optimization
76
Part 76: Unwinding Arrays: The $unwind Stage, Array Flattening, and preserveNullAndEmptyArrays
77
Part 77: Multi-Collection Joins: The $lookup Stage for Left Outer Joins
78
Part 78: Uncorrelated Subqueries with $lookup: Complex Join Conditions and Pipeline Joins
79
Part 79: Correlated Subqueries with $lookup using let and pipeline Variables
80
Part 80: Merging Pipeline Results: The $out and $merge Stages for ETL and Materialized Views
81
Part 81: The $facet Stage: Multi-Faceted Categorization and Search Result Aggregation
82
Part 82: Categorization Stages: $bucket and $bucketAuto for Histograms and Range Bucketing
83
Part 83: String and Regex Operators in Aggregation: $concat, $substr, $regexMatch, $toUpper
84
Part 84: Arithmetic and Date Operators in Aggregation: $dateToString, $dateDiff, $dateTrunc
85
Part 85: Conditional Expressions in Aggregation: $cond, $switch, and $ifNull
86
Part 86: Array Transformation Operators in Aggregation: $filter, $map, $reduce, and $concatArrays
87
Part 87: Window Functions in Aggregation: $setWindowFields for Moving Averages, Ranks, and Running Totals
88
Part 88: Aggregation Pipeline Performance Optimization, Memory Limits, and allowDiskUse
89
Part 89: Data Modeling in MongoDB: Embedding (Denormalization) vs Referencing (Normalization)
90
Part 90: One-to-One Relationships: When to Embed vs When to Reference
91
Part 91: One-to-Many Relationships: Embedding (Few), Referencing (Many), and Two-Way Referencing
92
Part 92: Many-to-Many Relationships: Array References, Linking Collections, and Hybrid Models
93
Part 93: Schema Design Pattern: The Polymorphic Pattern for Heterogeneous Catalogs
94
Part 94: Schema Design Pattern: The Attribute Pattern for Dynamic, Multi-Tenant E-Commerce
95
Part 95: Schema Design Pattern: The Bucket Pattern for Time Series and Sensor Data
96
Part 96: Schema Design Pattern: The Outlier Pattern for Handling Popularity Spikes (Celebrity Problem)
97
Part 97: Schema Design Pattern: The Subset Pattern for Mobile Devices and Small Caches
98
Part 98: Schema Design Pattern: The Extended Reference Pattern for Reducing $lookup Joins
99
Part 99: Schema Design Pattern: The Computed Pattern for Fast Read Latencies
100
Part 100: Tree and Hierarchical Data Modeling: Parent References, Child References, and Materialized Paths
101
Part 101: Schema Validation with JSON Schema: $jsonSchema Syntax, Types, and Required Fields
102
Part 102: Enforcing Validation Actions and Levels: error, warn, strict, and moderate
103
Part 103: ACID Guarantees in MongoDB: Single-Document Atomicity vs Multi-Document Transactions
104
Part 104: Multi-Document Distributed Transactions: Sessions, startTransaction, commit, and abort
105
Part 105: Write Concerns Explained: w:1, w:majority, w:0, and j:true Durability Settings
106
Part 106: Read Concerns Explained: local, available, majority, linearizable, and snapshot
107
Part 107: Read Preferences: primary, primaryPreferred, secondary, secondaryPreferred, and nearest
108
Part 108: Causal Consistency in Sessions: Read-Your-Own-Writes and Monotonic Reads
109
Part 109: Locking Architecture in WiredTiger: Document-Level Concurrency, Intent Locks, and Lock Queues
110
Part 110: Two-Phase Commits in MongoDB: Legacy Emulation vs Modern Distributed Transactions
111
Part 111: Transaction Limits and Best Practices: 60-Second Timeout and Payload Size Constraints
112
Part 112: Change Streams: Real-Time Change Data Capture (CDC), Resume Tokens, and Filtering
113
Part 113: Change Streams in Microservices: Event-Driven Architectures and Cache Invalidation
114
Part 114: Optimistic vs Pessimistic Locking Patterns for High-Contention Inventory Workflows
115
Part 115: Replica Set Architecture: Primary Nodes, Secondary Nodes, and Quorum
116
Part 116: The Replication Oplog (local.oplog.rs): Capped Collection Internals and Replication Lag
117
Part 117: Leader Election Mechanics: Raft-like Consensus, Heartbeats, and Priority Settings
118
Part 118: Deploying a 3-Node Replica Set Locally and in Production Environments
119
Part 119: Replica Set Member Types: Secondary-Only, Hidden Nodes, Delayed Nodes, and Arbiters
120
Part 120: Why Arbiters Should Be Avoided in Modern High-Availability Deployments
121
Part 121: Handling Network Partitions: Split-Brain Prevention and Majority Quorum Rules
122
Part 122: Monitoring Replication Lag: rs.status(), rs.printSecondaryReplicationInfo(), and Alerts
123
Part 123: Reconfiguring Replica Sets: rs.reconfig(), Adding/Removing Members with Zero Downtime
124
Part 124: Disaster Recovery in Replica Sets: Stepdown, Failover Testing, and Unclean Shutdowns
125
Part 125: Backup Strategies: mongodump/mongorestore, File System Snapshots, and Point-In-Time Restore
126
Part 126: Rolling Upgrades and Maintenance on Replica Sets Without Application Downtime
127
Part 127: Sharding Architecture: Shards, Config Database Servers, and Mongos Query Routers
128
Part 128: Choosing the Right Shard Key: Cardinality, Frequency, Monotonicity, and Query Isolation
129
Part 129: Ranged Sharding vs Hashed Sharding: Even Data Distribution vs Range Query Efficiency
130
Part 130: Compound Shard Keys: Combining High Cardinality with Query Routing Optimization
131
Part 131: Chunks, Jumbo Chunks, and the Automatic Chunk Balancer Mechanics
132
Part 132: Targeted Queries (Single-Shard Routing) vs Scatter-Gather Queries Across All Shards
133
Part 133: Tag-Aware Sharding / Zone Sharding: Geographic Data Sovereignty and Tiered Storage
134
Part 134: Refining and Changing Shard Keys in Modern MongoDB Deployments
135
Part 135: Sharding Collections: sh.enableSharding() and sh.shardCollection() Step-by-Step
136
Part 136: Diagnosing Sharded Clusters: sh.status(), Balancer Windows, and Chunk Splits
137
Part 137: Transactions in Sharded Clusters: Two-Phase Commit Across Distributed Shards
138
Part 138: Capacity Planning and Sharding Thresholds: When to Shard vs When to Scale Up
139
Part 139: Security Checklist: Authentication, Authorization, Network Hardening, and Auditing
140
Part 140: Role-Based Access Control (RBAC): Built-in Roles (readWrite, dbAdmin, userAdminAnyDatabase)
141
Part 141: Creating Custom Roles and Managing Users with Specific Granular Privileges
142
Part 142: Authentication Mechanisms: SCRAM-SHA-1, SCRAM-SHA-256, x.509 Certificates, and LDAP
143
Part 143: Network Security: Binding IPs, Firewalls, TLS/SSL Certificate Configuration
144
Part 144: Encryption at Rest: WiredTiger Storage Engine Encryption and Key Management (KMIP, AWS KMS)
145
Part 145: Client-Side Field Level Encryption (CSFLE): Automatic vs Explicit Encryption
146
Part 146: Queryable Encryption: Searching Encrypted BSON Documents Without Server-Side Decryption
147
Part 147: Introduction to MongoDB Atlas: Cloud Clusters, Global Clusters, and Serverless Instances
148
Part 148: Atlas Vector Search: Storing High-Dimensional AI/LLM Embeddings in MongoDB
149
Part 149: Vector Search Indexing: Hierarchical Navigable Small World (HNSW) and Approximate Nearest Neighbor
150
Part 150: Building AI Search and Retrieval-Augmented Generation (RAG) Pipelines with MongoDB Vector Search
151
Part 151: Atlas Full-Text Search with Apache Lucene: Custom Analyzers, Synonyms, and Autocomplete
152
Part 152: Atlas Triggers and Serverless Functions: Automated Event-Driven Workflows
153
Part 153: Node.js Native Driver Masterclass: MongoClient, Connection Pooling, and Typed Collections
154
Part 154: Mongoose ODM Deep Dive: Schemas, Models, Middlewares (Pre/Post Hooks), and Virtuals
155
Part 155: Mongoose Population vs Native $lookup: Performance Trade-offs and Best Practices
156
Part 156: PyMongo Masterclass: Python Integration, Cursor Iteration, and Pandas DataFrames
157
Part 157: Spring Data MongoDB for Java Developers: MongoTemplate, Repositories, and Mapping
158
Part 158: Database Profiling and Diagnostics: system.profile, mongostat, and mongotop Commands
159
Part 159: Performance Tuning WiredTiger Cache: cacheSizeGB, Dirty Pages, and Memory Sizing
160
Part 160: Enterprise Production Checklist: Top 25 Anti-Patterns and Best Practices in MongoDB
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  4. Part 1: Introduction to MongoDB: NoSQL Architecture, Document Model, and BSON Fundamentals

Part 1: Introduction to MongoDB: NoSQL Architecture, Document Model, and BSON Fundamentals

Part 1 Technology Updated September 19, 2026

Part 1: Introduction to MongoDB

Comprehensive guide to MongoDB architecture and document storage.

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