MongoDB vs phpMyAdmin

Overview

MongoDB

Stacks96.6K

Followers82.0K

Votes4.1K

GitHub Stars27.7K

Forks5.7K

phpMyAdmin

Stacks351

Followers307

Votes15

MongoDB vs phpMyAdmin: What are the differences?

Introduction

MongoDB and phpMyAdmin are both popular database management systems, but they differ in several key aspects.

Data Model: MongoDB uses a document-based data model, where data is stored in flexible, JSON-like documents. On the other hand, phpMyAdmin uses a traditional relational data model, with data organized into tables comprising rows and columns.
Schema: MongoDB is schema-less, allowing you to store different types of data in the same collection without a predefined structure. phpMyAdmin, on the other hand, requires a predefined schema before data can be inserted into its tables.
Query Language: MongoDB uses a rich and powerful query language known as MongoDB Query Language (MQL). It supports complex queries, indexing, and aggregation operations. In contrast, phpMyAdmin uses SQL (Structured Query Language) for querying and managing the database.
Scalability: MongoDB is designed to scale horizontally, allowing you to distribute data across multiple servers and handle large amounts of traffic. phpMyAdmin typically runs on a single server and can experience performance issues when dealing with high loads of data or traffic.
Hosting: MongoDB is a document-oriented database that can be hosted either on-premise or in the cloud. It offers various cloud-based hosting options like MongoDB Atlas. phpMyAdmin, on the other hand, is typically hosted on a web server and requires PHP and MySQL to function.
Data Validation: MongoDB allows dynamic schemas and flexible data types, which means it does not enforce strict validation rules on the data being inserted. phpMyAdmin, on the other hand, enforces strict data types and has predefined constraints to ensure data integrity.

In summary, MongoDB and phpMyAdmin differ in terms of data model, schema, query language, scalability, hosting options, and data validation.

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Advice on MongoDB, phpMyAdmin

George

Student

Mar 18, 2020

Needs adviceon

PostgreSQL

Python

Django

Hello everyone,

Well, I want to build a large-scale project, but I do not know which ORDBMS to choose. The app should handle real-time operations, not chatting, but things like future scheduling or reminders. It should be also really secure, fast and easy to use. And last but not least, should I use them both. I mean PostgreSQL with Python / Django and MongoDB with Node.js? Or would it be better to use PostgreSQL with Node.js?

*The project is going to use React for the front-end and GraphQL is going to be used for the API.

Thank you all. Any answer or advice would be really helpful!

620k views620k

Comments

Ido

Mar 6, 2020

Decided

My data was inherently hierarchical, but there was not enough content in each level of the hierarchy to justify a relational DB (SQL) with a one-to-many approach. It was also far easier to share data between the frontend (Angular), backend (Node.js) and DB (MongoDB) as they all pass around JSON natively. This allowed me to skip the translation layer from relational to hierarchical. You do need to think about correct indexes in MongoDB, and make sure the objects have finite size. For instance, an object in your DB shouldn't have a property which is an array that grows over time, without limit. In addition, I did use MySQL for other types of data, such as a catalog of products which (a) has a lot of data, (b) flat and not hierarchical, (c) needed very fast queries.

575k views575k

Comments

Mike

Mar 20, 2020

Needs advice

We Have thousands of .pdf docs generated from the same form but with lots of variability. We need to extract data from open text and more important - from tables inside the docs. The output of Couchbase/Mongo will be one row per document for backend processing. ADOBE renders the tables in an unusable form.

241k views241k

Comments

Detailed Comparison

MongoDB	phpMyAdmin
MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.	As a portable web application written primarily in PHP, it has become one of the most popular MySQL administration tools, especially for web hosting services.
Flexible data model, expressive query language, secondary indexes, replication, auto-sharding, in-place updates, aggregation, GridFS	-
Statistics
GitHub Stars 27.7K	GitHub Stars -
GitHub Forks 5.7K	GitHub Forks -
Stacks 96.6K	Stacks 351
Followers 82.0K	Followers 307
Votes 4.1K	Votes 15
Pros & Cons
Pros 829 Document-oriented storage 594 No sql 554 Ease of use 465 Fast 410 High performance Cons 6 Very slowly for connected models that require joins 3 Not acid compliant 2 Proprietary query language	Pros 5 Easy data access 5 User administration 5 Query linter Cons 1 Insecure
Integrations
No integrations available	GitHub PHP Bootstrap MariaDB MySQL JavaScript Docker Hub jQuery PHPUnit PHPStan

What are some alternatives to MongoDB, phpMyAdmin?

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.

New Relic

The world’s best software and DevOps teams rely on New Relic to move faster, make better decisions and create best-in-class digital experiences. If you run software, you need to run New Relic. More than 50% of the Fortune 100 do too.

dbForge Studio for MySQL

It is the universal MySQL and MariaDB client for database management, administration and development. With the help of this intelligent MySQL client the work with data and code has become easier and more convenient. This tool provides utilities to compare, synchronize, and backup MySQL databases with scheduling, and gives possibility to analyze and report MySQL tables data.

Datadog

Datadog is the leading service for cloud-scale monitoring. It is used by IT, operations, and development teams who build and operate applications that run on dynamic or hybrid cloud infrastructure. Start monitoring in minutes with Datadog!

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

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MongoDB vs phpMyAdmin: What are the differences?

Introduction

MongoDB and phpMyAdmin are both popular database management systems, but they differ in several key aspects.

Data Model: MongoDB uses a document-based data model, where data is stored in flexible, JSON-like documents. On the other hand, phpMyAdmin uses a traditional relational data model, with data organized into tables comprising rows and columns.
Schema: MongoDB is schema-less, allowing you to store different types of data in the same collection without a predefined structure. phpMyAdmin, on the other hand, requires a predefined schema before data can be inserted into its tables.
Query Language: MongoDB uses a rich and powerful query language known as MongoDB Query Language (MQL). It supports complex queries, indexing, and aggregation operations. In contrast, phpMyAdmin uses SQL (Structured Query Language) for querying and managing the database.
Scalability: MongoDB is designed to scale horizontally, allowing you to distribute data across multiple servers and handle large amounts of traffic. phpMyAdmin typically runs on a single server and can experience performance issues when dealing with high loads of data or traffic.
Hosting: MongoDB is a document-oriented database that can be hosted either on-premise or in the cloud. It offers various cloud-based hosting options like MongoDB Atlas. phpMyAdmin, on the other hand, is typically hosted on a web server and requires PHP and MySQL to function.
Data Validation: MongoDB allows dynamic schemas and flexible data types, which means it does not enforce strict validation rules on the data being inserted. phpMyAdmin, on the other hand, enforces strict data types and has predefined constraints to ensure data integrity.

In summary, MongoDB and phpMyAdmin differ in terms of data model, schema, query language, scalability, hosting options, and data validation.