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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. MySQL vs RethinkDB

MySQL vs RethinkDB

OverviewDecisionsComparisonAlternatives

Overview

RethinkDB
RethinkDB
Stacks292
Followers406
Votes307
GitHub Stars27.0K
Forks1.9K
MySQL
MySQL
Stacks129.6K
Followers108.6K
Votes3.8K
GitHub Stars11.8K
Forks4.1K

MySQL vs RethinkDB: What are the differences?

Introduction

MySQL and RethinkDB are both popular database management systems, but they have key differences in terms of functionality and design. In this Markdown code, we will highlight six of these differences in a concise and specific manner.

  1. Data Model: MySQL follows a traditional relational data model, utilizing structured tables with predefined schemas consisting of rows and columns. On the other hand, RethinkDB adopts a schema-less approach called a document data model, where data is stored as flexible JSON-like documents within collections.

  2. Real-time Capabilities: RethinkDB distinguishes itself by natively supporting real-time change feeds. Developers can subscribe to these feeds and receive updates in real-time whenever changes occur in the database. MySQL, however, does not provide such built-in functionality, requiring extra effort to achieve real-time capabilities.

  3. Horizontal Scaling: MySQL primarily relies on vertical scaling, which involves adding more computing power to a single server to handle increased workloads. RethinkDB, in contrast, offers built-in support for horizontal scaling, enabling data distribution across multiple machines to improve performance and handle larger workloads.

  4. Query Language: MySQL employs Structured Query Language (SQL) as its primary query language, a widely adopted standard for managing and querying relational databases. On the other hand, RethinkDB provides its own query language called ReQL (RethinkDB Query Language), which is specifically designed to manipulate and retrieve data from JSON-like documents.

  5. Fault Tolerance: RethinkDB provides automatic data replication and distribution, ensuring fault tolerance and high availability by default. When a server fails, it automatically replicates and redistributes data across other servers in the cluster. MySQL, in contrast, requires additional configuration and setup to achieve fault tolerance.

  6. Consistency Model: MySQL follows an ACID (Atomicity, Consistency, Isolation, Durability) consistency model, where data is ensured to be consistent and predictable at all times. RethinkDB utilizes a more relaxed, 'eventually consistent' model, which provides high availability and low latency at the cost of ensuring immediate consistency.

In Summary, MySQL and RethinkDB differ in terms of their data model, real-time capabilities, scalability options, query languages, fault tolerance mechanisms, and consistency models.

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Advice on RethinkDB, MySQL

Kyle
Kyle

Web Application Developer at Redacted DevWorks

Dec 3, 2019

DecidedonPostGISPostGIS

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
Ido
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
Navraj
Navraj

CEO at SuPragma

Apr 16, 2020

Needs adviceonMySQLMySQLPostgreSQLPostgreSQL

I asked my last question incorrectly. Rephrasing it here.

I am looking for the most secure open source database for my project I'm starting: https://github.com/SuPragma/SuPragma/wiki

Which database is more secure? MySQL or PostgreSQL? Are there others I should be considering? Is it possible to change the encryption keys dynamically?

Thanks,

Raj

401k views401k
Comments

Detailed Comparison

RethinkDB
RethinkDB
MySQL
MySQL

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.

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.

JSON data model and immediate consistency.;Distributed joins, subqueries, aggregation, atomic updates.;Secondary, compound, and arbitrarily computed indexes.;Hadoop-style map/reduce.;Friendly web and command-line administration tools.;Takes care of machine failures and network interrupts.;Multi-datacenter replication and failover.;Sharding and replication to multiple nodes.;Queries are automatically parallelized and distributed.;Lock-free operation via MVCC concurrency.
-
Statistics
GitHub Stars
27.0K
GitHub Stars
11.8K
GitHub Forks
1.9K
GitHub Forks
4.1K
Stacks
292
Stacks
129.6K
Followers
406
Followers
108.6K
Votes
307
Votes
3.8K
Pros & Cons
Pros
  • 48
    Powerful query language
  • 46
    Excellent dashboard
  • 42
    JSON
  • 41
    Distributed database
  • 38
    Open source
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
Integrations
Amazon EC2
Amazon EC2
No integrations available

What are some alternatives to RethinkDB, MySQL?

MongoDB

MongoDB

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.

PostgreSQL

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

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

SQLite

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

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

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

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.

ArangoDB

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

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

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.

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