MongoDB vs MySQL vs SQLite

Overview

MySQL

Stacks129.6K

Followers108.6K

Votes3.8K

GitHub Stars11.8K

Forks4.1K

MongoDB

Stacks96.6K

Followers82.0K

Votes4.1K

GitHub Stars27.7K

Forks5.7K

SQLite

Stacks19.9K

Followers15.2K

Votes535

MongoDB vs MySQL vs SQLite: What are the differences?

MongoDB, MySQL, and SQLite are popular relational database management systems used in various applications. Each has its own set of features and capabilities that make it suitable for different use cases.

Data Model: MongoDB is a NoSQL database that uses a document-based model, allowing for flexible and dynamic schemas. MySQL and SQLite are relational databases that use a structured schema with tables, rows, and columns.
Scaling: MongoDB is better suited for scalable applications due to its horizontal scaling capabilities and distributed architecture. MySQL and SQLite are more suitable for smaller-scale applications that do not require extensive scaling.
Query Language: MongoDB uses a query language that is similar to JSON, making it easy to work with for developers. MySQL and SQLite use SQL, which is a standardized language for managing relational databases.
ACID Compliance: MySQL and SQLite are ACID compliant, ensuring reliable transactions and data integrity. MongoDB sacrifices ACID compliance for performance and scalability, making it more suitable for certain use cases where data consistency is not a top priority.
Community and Support: MySQL has a large and active community with extensive documentation and support resources available. MongoDB also has a strong community, but SQLite may lack some of the robust support systems that MySQL and MongoDB offer.
Use Cases: MongoDB is ideal for applications that involve large amounts of unstructured data and require high scalability. MySQL and SQLite are better suited for traditional relational database applications that require strict consistency and data integrity.

In Summary, MongoDB, MySQL, and SQLite differ in their data models, scalability, query languages, ACID compliance, community support, and use cases, making them suitable for various types of applications.

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Advice on MySQL, MongoDB, SQLite

Kyle

Web Application Developer at Redacted DevWorks

Dec 3, 2019

Decidedon

PostGIS

While there's been some very clever techniques that has allowed non-natively supported geo querying to be performed, it is incredibly slow in the long game and error prone at best.

MySQL finally introduced it's own GEO functions and special indexing operations for GIS type data. I prototyped with this, as MySQL is the most familiar database to me. But no matter what I did with it, how much tuning i'd give it, how much I played with it, the results would come back inconsistent.

It was very disappointing.

I figured, at this point, that SQL Server, being an enterprise solution authored by one of the biggest worldwide software developers in the world, Microsoft, might contain some decent GIS in it.

I was very disappointed.

Postgres is a Database solution i'm still getting familiar with, but I noticed it had no built in support for GIS. So I hilariously didn't pay it too much attention. That was until I stumbled upon PostGIS and my world changed forever.

449k views449k

Comments

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

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

MySQL	MongoDB	SQLite
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.	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.	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.
-	Flexible data model, expressive query language, secondary indexes, replication, auto-sharding, in-place updates, aggregation, GridFS	-
Statistics
GitHub Stars 11.8K	GitHub Stars 27.7K	GitHub Stars -
GitHub Forks 4.1K	GitHub Forks 5.7K	GitHub Forks -
Stacks 129.6K	Stacks 96.6K	Stacks 19.9K
Followers 108.6K	Followers 82.0K	Followers 15.2K
Votes 3.8K	Votes 4.1K	Votes 535
Pros & Cons
Pros 800 Sql 679 Free 562 Easy 528 Widely used 490 Open source Cons 16 Owned by a company with their own agenda 3 Can't roll back schema changes	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 163 Lightweight 135 Portable 122 Simple 81 Sql 29 Preinstalled on iOS and Android Cons 2 Not for multi-process of multithreaded apps 1 Needs different binaries for each platform

What are some alternatives to MySQL, MongoDB, SQLite?

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.

Microsoft SQL Server

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

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.

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

A distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions.

InfluxDB

InfluxDB is a scalable datastore for metrics, events, and real-time analytics. It has a built-in HTTP API so you don't have to write any server side code to get up and running. InfluxDB is designed to be scalable, simple to install and manage, and fast to get data in and out.

CouchDB

Apache CouchDB is a database that uses JSON for documents, JavaScript for MapReduce indexes, and regular HTTP for its API. CouchDB is a database that completely embraces the web. Store your data with JSON documents. Access your documents and query your indexes with your web browser, via HTTP. Index, combine, and transform your documents with JavaScript.

Oracle

Oracle Database is an RDBMS. An RDBMS that implements object-oriented features such as user-defined types, inheritance, and polymorphism is called an object-relational database management system (ORDBMS). Oracle Database has extended the relational model to an object-relational model, making it possible to store complex business models in a relational database.

Related Comparisons

MongoDB vs MySQL vs SQLite: What are the differences?

Data Model: MongoDB is a NoSQL database that uses a document-based model, allowing for flexible and dynamic schemas. MySQL and SQLite are relational databases that use a structured schema with tables, rows, and columns.
Scaling: MongoDB is better suited for scalable applications due to its horizontal scaling capabilities and distributed architecture. MySQL and SQLite are more suitable for smaller-scale applications that do not require extensive scaling.
Query Language: MongoDB uses a query language that is similar to JSON, making it easy to work with for developers. MySQL and SQLite use SQL, which is a standardized language for managing relational databases.
ACID Compliance: MySQL and SQLite are ACID compliant, ensuring reliable transactions and data integrity. MongoDB sacrifices ACID compliance for performance and scalability, making it more suitable for certain use cases where data consistency is not a top priority.
Community and Support: MySQL has a large and active community with extensive documentation and support resources available. MongoDB also has a strong community, but SQLite may lack some of the robust support systems that MySQL and MongoDB offer.
Use Cases: MongoDB is ideal for applications that involve large amounts of unstructured data and require high scalability. MySQL and SQLite are better suited for traditional relational database applications that require strict consistency and data integrity.

MongoDB vs MySQL vs SQLite

Overview