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

MySQL vs Vitess

OverviewDecisionsComparisonAlternatives

Overview

MySQL
MySQL
Stacks129.6K
Followers108.6K
Votes3.8K
GitHub Stars11.8K
Forks4.1K
Vitess
Vitess
Stacks66
Followers166
Votes0

MySQL vs Vitess: What are the differences?

  1. Key difference 1: Scalability: MySQL is a traditional relational database management system (RDBMS) that can handle small to medium-sized workloads but faces challenges when dealing with large-scale applications that require high scalability. On the other hand, Vitess is an open-source database clustering system that extends MySQL to achieve horizontal scalability, allowing it to handle massive workloads and distribute data across multiple servers efficiently.

  2. Key difference 2: Sharding: MySQL lacks built-in sharding capabilities, which means that when the database grows beyond the capabilities of a single machine, it becomes challenging to scale efficiently. In contrast, Vitess provides automatic sharding, allowing it to partition the data across multiple instances and distribute the load evenly. This enables Vitess to handle larger datasets and provide improved performance compared to MySQL in a sharded setup.

  3. Key difference 3: High Availability: While MySQL supports replication for achieving high availability, it requires manual configuration and management. On the other hand, Vitess offers built-in fault tolerance and resiliency, providing automatic replication and failover capabilities. This makes Vitess a more suitable choice for applications that require high availability with minimal manual intervention.

  4. Key difference 4: Query Routing: In a traditional MySQL setup, the application is responsible for routing queries to the appropriate database server, leading to complex and error-prone code. Vitess, on the other hand, acts as a middleware layer that transparently routes queries based on the sharding scheme. This simplifies the application code and eliminates the need for manual query routing, making it easier to scale and manage the database.

  5. Key difference 5: Online Schema Changes: Performing schema changes in MySQL can often be time-consuming and may require downtime or application-level changes. Vitess provides efficient online schema changes, allowing database schema modifications to be performed without impacting the availability of the system. This enables applications to adapt to evolving requirements without interrupting user access to the data.

  6. Key difference 6: Tools and Ecosystem: MySQL has a rich ecosystem with a wide range of tools and libraries available for various purposes, such as monitoring, backup/restore, and administration. While Vitess leverages many of MySQL's existing tools, it also provides additional tools specifically designed for deploying, managing, and monitoring a Vitess cluster. These tools enhance the operational capabilities and ease the management of a Vitess-based deployment.

In Summary, MySQL lacks native scalability and sharding capabilities, requires manual configuration for achieving high availability, lacks automatic query routing, has limitations in executing online schema changes, and relies on a broader ecosystem of tools. On the other hand, Vitess addresses these limitations by providing horizontal scalability, automatic sharding, built-in high availability, transparent query routing, efficient online schema changes, and a specialized set of tools.

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Advice on MySQL, Vitess

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

MySQL
MySQL
Vitess
Vitess

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.

It is a database solution for deploying, scaling and managing large clusters of MySQL instances. It’s architected to run as effectively in a public or private cloud architecture as it does on dedicated hardware. It combines and extends many important MySQL features with the scalability of a NoSQL database.

-
Scalability; Connection pooling; Manageability
Statistics
GitHub Stars
11.8K
GitHub Stars
-
GitHub Forks
4.1K
GitHub Forks
-
Stacks
129.6K
Stacks
66
Followers
108.6K
Followers
166
Votes
3.8K
Votes
0
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
No community feedback yet
Integrations
No integrations available
Amazon RDS
Amazon RDS
Kubernetes
Kubernetes

What are some alternatives to MySQL, Vitess?

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.

RethinkDB

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

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.

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