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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Azure SQL Database vs MySQL

Azure SQL Database vs MySQL

OverviewDecisionsComparisonAlternatives

Overview

MySQL
MySQL
Stacks129.6K
Followers108.6K
Votes3.8K
GitHub Stars11.8K
Forks4.1K
Azure SQL Database
Azure SQL Database
Stacks585
Followers502
Votes13

Azure SQL Database vs MySQL: What are the differences?

Introduction

When choosing a database management system for your application, it's essential to understand the key differences between Azure SQL Database and MySQL in order to make an informed decision.

  1. Hosting and Management: Azure SQL Database is a fully managed database service provided by Microsoft in the cloud, allowing users to focus on their applications instead of managing the infrastructure. In contrast, MySQL is an open-source relational database management system that can be self-hosted or managed through third-party cloud services like Amazon RDS or Google Cloud SQL.

  2. Scalability and Performance: Azure SQL Database offers built-in automatic scaling, allowing users to adjust resources based on workload demands, while MySQL requires manual intervention to scale resources by either vertically scaling up the server or sharding data horizontally. This difference in scalability approach can impact performance optimization in handling high traffic loads.

  3. Storage Limit: Azure SQL Database has a storage limit that varies based on the chosen service tier, with options for scaling up to meet storage requirements. On the other hand, MySQL imposes no specific storage limit, allowing users to manage storage based on the hardware and configurations of the host server or cloud environment where it is deployed.

  4. Pricing Model: Azure SQL Database operates on a pay-as-you-go pricing model, where users are billed based on the resources consumed, including storage and compute resources. In contrast, MySQL is typically free to use under the open-source license, but users may incur costs for infrastructure services when self-hosting or opting for managed services.

  5. Security Features: Azure SQL Database provides advanced security features such as data encryption, threat detection, and transparent data encryption to ensure data protection and compliance with regulations. While MySQL also supports encryption and security measures, users may need to implement additional security controls based on their deployment environment and configuration.

  6. Supported Database Engines: Azure SQL Database is based on the Microsoft SQL Server engine, offering compatibility with T-SQL and support for features like SQL Server Analysis Services and Reporting Services. On the other hand, MySQL uses the InnoDB storage engine by default, with the option to use other engines like MyISAM, which may impact performance and feature support in certain scenarios.

In Summary, understanding the differences between Azure SQL Database and MySQL in terms of hosting, scalability, storage, pricing, security, and supported database engines can help in selecting the right database solution for your application based on specific requirements and preferences.

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Advice on MySQL, Azure SQL Database

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
Azure SQL Database
Azure SQL Database

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 the intelligent, scalable, cloud database service that provides the broadest SQL Server engine compatibility and up to a 212% return on investment. It is a database service that can quickly and efficiently scale to meet demand, is automatically highly available, and supports a variety of third party software.

Statistics
GitHub Stars
11.8K
GitHub Stars
-
GitHub Forks
4.1K
GitHub Forks
-
Stacks
129.6K
Stacks
585
Followers
108.6K
Followers
502
Votes
3.8K
Votes
13
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
  • 6
    Managed
  • 4
    Secure
  • 3
    Scalable

What are some alternatives to MySQL, Azure SQL Database?

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.

Amazon RDS

Amazon RDS

Amazon RDS gives you access to the capabilities of a familiar MySQL, Oracle or Microsoft SQL Server database engine. This means that the code, applications, and tools you already use today with your existing databases can be used with Amazon RDS. Amazon RDS automatically patches the database software and backs up your database, storing the backups for a user-defined retention period and enabling point-in-time recovery. You benefit from the flexibility of being able to scale the compute resources or storage capacity associated with your Database Instance (DB Instance) via a single API call.

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.

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