Couchbase vs MongoDB vs MySQL

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

Couchbase

Stacks505

Followers606

Votes110

Couchbase vs MongoDB vs MySQL: What are the differences?

## Key Differences between Couchbase, MongoDB, and MySQL

Couchbase, MongoDB, and MySQL are popular databases that serve different purposes and come with various features. Below are the key differences between them.

1. **Data Model**: Couchbase and MongoDB are NoSQL databases, allowing for flexible schemas, while MySQL is a relational database, enforcing a structured schema with predefined tables, columns, and relationships.
2. **Scalability**: Couchbase and MongoDB are designed for horizontal scalability, enabling them to handle large amounts of data by distributing it across multiple nodes, whereas MySQL traditionally scales vertically, requiring more powerful hardware as data grows.
3. **Query Language**: Couchbase and MongoDB use query languages specific to their databases, such as N1QL for Couchbase and the MongoDB Query Language. MySQL uses SQL, which is a standard language for relational databases.
4. **Consistency**: Couchbase and MongoDB offer eventual consistency by default, where data may be inconsistent across nodes in a cluster before it is eventually synchronized. MySQL offers strong consistency by default, ensuring that all data operations are immediately consistent across all nodes.
5. **Use Cases**: Couchbase and MongoDB are often used for applications requiring high availability, fast reads, and occasional updates, such as mobile apps or real-time analytics. MySQL is suitable for transactional applications that require complex queries, ACID compliance, and structured data.
6. **Data Distribution**: Couchbase and MongoDB support automatic sharding for distributing data across multiple nodes, allowing for better performance and fault tolerance. MySQL relies on manual partitioning for distributing data, which can be more complex and less flexible.

In Summary, the key differences between Couchbase, MongoDB, and MySQL lie in their data models, scalability, query languages, consistency models, use cases, and data distribution strategies.

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Advice on MySQL, MongoDB, Couchbase

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

Gabriel

CEO at Naologic

Jan 2, 2020

Decidedon

CouchDB

Couchbase

Memcached

We implemented our first large scale EPR application from naologic.com using CouchDB .

Very fast, replication works great, doesn't consume much RAM, queries are blazing fast but we found a problem: the queries were very hard to write, it took a long time to figure out the API, we had to go and write our own @nodejs library to make it work properly.

It lost most of its support. Since then, we migrated to Couchbase and the learning curve was steep but all worth it. Memcached indexing out of the box, full text search works great.

592k views592k

Comments

Detailed Comparison

MySQL	MongoDB	Couchbase
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.	Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.
-	Flexible data model, expressive query language, secondary indexes, replication, auto-sharding, in-place updates, aggregation, GridFS	JSON document database; N1QL (SQL-like query language); Secondary Indexing; Full-Text Indexing; Eventing/Triggers; Real-Time Analytics; Mobile Synchronization for offline support; Autonomous Operator for Kubernetes and OpenShift
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 505
Followers 108.6K	Followers 82.0K	Followers 606
Votes 3.8K	Votes 4.1K	Votes 110
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 18 Flexible data model, easy scalability, extremely fast 18 High performance 9 Mobile app support 7 You can query it with Ansi-92 SQL 6 All nodes can be read/write Cons 3 Terrible query language
Integrations
No integrations available	No integrations available	Hadoop Kafka Elasticsearch Kubernetes Apache Spark

What are some alternatives to MySQL, MongoDB, Couchbase?

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.

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.

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.

Related Comparisons

Couchbase vs MongoDB vs MySQL: What are the differences?

## Key Differences between Couchbase, MongoDB, and MySQL

Couchbase, MongoDB, and MySQL are popular databases that serve different purposes and come with various features. Below are the key differences between them.

1. **Data Model**: Couchbase and MongoDB are NoSQL databases, allowing for flexible schemas, while MySQL is a relational database, enforcing a structured schema with predefined tables, columns, and relationships.
2. **Scalability**: Couchbase and MongoDB are designed for horizontal scalability, enabling them to handle large amounts of data by distributing it across multiple nodes, whereas MySQL traditionally scales vertically, requiring more powerful hardware as data grows.
3. **Query Language**: Couchbase and MongoDB use query languages specific to their databases, such as N1QL for Couchbase and the MongoDB Query Language. MySQL uses SQL, which is a standard language for relational databases.
4. **Consistency**: Couchbase and MongoDB offer eventual consistency by default, where data may be inconsistent across nodes in a cluster before it is eventually synchronized. MySQL offers strong consistency by default, ensuring that all data operations are immediately consistent across all nodes.
5. **Use Cases**: Couchbase and MongoDB are often used for applications requiring high availability, fast reads, and occasional updates, such as mobile apps or real-time analytics. MySQL is suitable for transactional applications that require complex queries, ACID compliance, and structured data.
6. **Data Distribution**: Couchbase and MongoDB support automatic sharding for distributing data across multiple nodes, allowing for better performance and fault tolerance. MySQL relies on manual partitioning for distributing data, which can be more complex and less flexible.

In Summary, the key differences between Couchbase, MongoDB, and MySQL lie in their data models, scalability, query languages, consistency models, use cases, and data distribution strategies.

Couchbase vs MongoDB vs MySQL

Overview