Educational repository demonstrating approaches for storing tree structures with NoSQL database MongoDB

Implementing Tree Structure in MongoDB

Storing and retrieving tree structures with MongoDB

A modern, secure, full-stack application for organizing notes and tasks in a hierarchical tree structure. Built with React, Node.js, and MongoDB.

A full-stack Vue.js application implementing mongoDB, mongoose, node, node express, socket.io and other technologies to create a persistent, live-updating application with a tree structure.

A tree like structure key value database powered by SQLite, LevelDB, MongoDB etc，with TTL support

Hello everyone 👋! This application is a whatsapp chatbot integrated with mongodb, it uses mongodb to store menus and options, besides it uses a data structure, a n-ary tree for menu navigation. Also this app has an api for mongodb data management.

Manage tree structures in MongoDB

Simple App that allows to upload video files and store them in MongoDB using GridFS. Files organized as folders tree structure. MERN stack

Java8 features+ Spring + Angular + PL/SQL, MySQL + NoSQL, MongoDB+ Python3, HTML, CSS, PHP,C/C++,Fortran - Data Structures and Algorithms, OOP concepts; Time Complexity, Linked List, Stacks, Queue, Binary Tree, Heap, Selection sort, Bubble sort, Insertion sort, shell sort, Merge sort, Quick sort, Binary tree sort, Heap sort, Linear & Binary search

Used JavaScript functions to populate collections. To increase query performance, used B-Tree (range) and geospatial indexing. Ran aggregated queries to return structures exclusive of individual documents. Used MongoDB’s version of MapReduce to fetch distinct digit counts for phone numbers in an extensively large dataset.

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Python module for tree structures in MongoDB

MongoDB GraphQL Tree Structure Data Management App.

Fullstack Folder Structure Viewer built with React, TypeScript, Express, and MongoDB. Visualize and manage hierarchical folder trees with CRUD API.

This is a simple NodeJS, Express & MongoDB project which search for the questions following under 1 category. (Tree data structure)

Deep dive into database internals: MySQL, PostgreSQL, MongoDB, Redis. Implementing core structures from scratch (B+tree, Skip List, MVCC, etc.)

Smart Family Tree Generator — Backend Node.js + Express + MongoDB API for family member management, relationship modeling, search, and JWT authentication. Provides structured data for D3.js-based tree visualization.

An application to load the entire tree structure from the ImageNet Fall 2011 release api, save all the nodes sequentially into a DB (MongoDB), and serve the tree to a single page app in ReactJS as a json.

I did this project for a interview task. I built a tree folder structure here. Where user can creates another folder inside a folder. User can also delete any folder excepts the root folder. I used mongoDB tree data structure to build this. For deployment I used firebase, heroku, and netlify.

I did this project for a interview task. I built a tree folder structure here. Where user can creates another folder inside a folder. User can also delete any folder excepts the root folder. I used mongoDB tree data structure to build this. For deployment I used firebase, heroku, and netlify.

Backend for a Multi-Level Marketing (MLM) System using Binary Tree structure. Built with Node.js, Express, and MongoDB — supports member joining, spill logic, sponsor hierarchy, and left/right downline tracking.

MiniDBGo is a lightweight, educational database engine written in Go, inspired by MongoDB. This project is designed as a learning resource to understand core database internals such as CRUD operations, durability through Write-Ahead Logs (WAL), and the storage architecture of a Log-Structured Merge-Tree (LSM-Tree).

This project is a 3-tier rule engine application built using Node.js for the backend and MongoDB for data storage. It leverages an Abstract Syntax Tree (AST) structure to represent and evaluate complex conditional rules for determining user eligibility.

The AST Manager Project is a system that allows users to create, combine, and evaluate Abstract Syntax Trees (ASTs) based on logical rules. It is built using a React frontend and a Node.js backend with MongoDB as the database. The AST structure is converted into JSON, which is both returned to the user and stored in the MongoDB database.

The project is a 3-tier rule engine application that allows users to input eligibility rules via a React frontend, stores the rules in a MongoDB database, and processes them using a Node.js/Express backend with an Abstract Syntax Tree (AST) structure. It evaluates user attributes like age and income to determine eligibility based on dynamic rules.