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  1. Stackups
  2. Application & Data
  3. Databases
  4. Databases
  5. Microsoft SQL Server vs MySQL vs PostgreSQL

Microsoft SQL Server vs MySQL vs PostgreSQL

OverviewDecisionsComparisonAlternatives

Overview

MySQL
MySQL
Stacks129.6K
Followers108.6K
Votes3.8K
GitHub Stars11.8K
Forks4.1K
Microsoft SQL Server
Microsoft SQL Server
Stacks21.3K
Followers15.5K
Votes540
PostgreSQL
PostgreSQL
Stacks103.0K
Followers83.9K
Votes3.6K
GitHub Stars19.0K
Forks5.2K

Microsoft SQL Server vs MySQL vs PostgreSQL: What are the differences?

Introduction

Microsoft SQL Server, MySQL, and PostgreSQL are three popular and widely used relational database management systems (RDBMS). While all three are capable of handling large amounts of data and offer various features, there are several key differences that set them apart.

  1. Data Types and Functions: Microsoft SQL Server, MySQL, and PostgreSQL offer different data types and functions. For example, Microsoft SQL Server has its own unique data types like datetime2 and money that are not available in MySQL and PostgreSQL. Similarly, MySQL has its own data types like ENUM and SET which are not found in the other two database systems. Additionally, each RDBMS has its own set of built-in functions that may differ from one another.

  2. Transaction Management: While all three database systems support transactions, there are differences in how they handle them. Microsoft SQL Server uses the BEGIN TRANSACTION, COMMIT, and ROLLBACK statements to manage transactions. On the other hand, MySQL and PostgreSQL use the START TRANSACTION, COMMIT, and ROLLBACK statements. Additionally, PostgreSQL supports savepoints within a transaction, which allows for more granular control over transaction rollback.

  3. Concurrency Control: Concurrency control is the ability of a database system to handle multiple transactions concurrently while maintaining data consistency. Microsoft SQL Server, MySQL, and PostgreSQL use different methods to achieve concurrency control. SQL Server uses locking and multiversion concurrency control (MVCC) to manage concurrency. MySQL primarily relies on locking, but it also supports MVCC for some storage engines. PostgreSQL is known for its advanced MVCC implementation, allowing for higher concurrency and better scalability.

  4. Replication: Replication is the process of copying and synchronizing data across multiple database instances. Microsoft SQL Server, MySQL, and PostgreSQL offer different replication options. SQL Server has its own replication technology, which allows for various types of replication, such as snapshot replication and transactional replication. MySQL provides replication capabilities through its native MySQL replication, which supports master-slave replication. PostgreSQL also supports master-slave replication, but it also offers more advanced options like logical replication and high availability solutions.

  5. Stored Procedures and Triggers: All three database systems support the use of stored procedures and triggers. However, there are differences in their implementation and syntax. Microsoft SQL Server uses Transact-SQL (T-SQL) for stored procedures and triggers, while MySQL uses its own dialect of SQL, which is similar to standard SQL. PostgreSQL supports stored procedures and triggers using various languages, including PL/pgSQL (similar to Oracle's PL/SQL) and other scripting languages like Python and Perl.

  6. Licensing and Cost: Another significant difference between the three database systems is the licensing and cost. Microsoft SQL Server is a commercial product and requires the purchase of licenses, which can be costly depending on the edition and number of user licenses needed. MySQL and PostgreSQL, on the other hand, are open-source and free to use, making them more cost-effective options for many organizations.

In Summary, Microsoft SQL Server, MySQL, and PostgreSQL differ in data types and functions, transaction management, concurrency control, replication options, stored procedures and triggers syntax, as well as licensing and cost.

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Advice on MySQL, Microsoft SQL Server, PostgreSQL

George
George

Student

Mar 18, 2020

Needs adviceonPostgreSQLPostgreSQLPythonPythonDjangoDjango

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
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
BrockHerion
BrockHerion

May 6, 2020

Needs adviceonMongoDBMongoDBPostgreSQLPostgreSQL

Hi everybody, I'm developing an application to be used in a gym setting where athletes fill out a health survey, and coaches can analyze the results. However, due to the dynamic nature of some aspects of the app and more static aspects of the other, I am wondering if/how I would integrate MongoDB with my existing PostgreSQL database. I would like to store things like registrations, license information, and club information in Postgres, while I am thinking about moving things like user surveys, logging, and user settings information over to MongoDB. Some fields on the survey are integers, some large blocks of text, and some are arrays. My thought is, if I moved that data to MongoDB, it would give us greater flexibility in terms of adding and removing fields and data to them, and it would scale a lot easier than Postgres. Not to mention it will be easier to organize that kind of data. Is that overkill or am I approaching this issue the right way? Thank you!

691k views691k
Comments

Detailed Comparison

MySQL
MySQL
Microsoft SQL Server
Microsoft SQL Server
PostgreSQL
PostgreSQL

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.

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

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.

Statistics
GitHub Stars
11.8K
GitHub Stars
-
GitHub Stars
19.0K
GitHub Forks
4.1K
GitHub Forks
-
GitHub Forks
5.2K
Stacks
129.6K
Stacks
21.3K
Stacks
103.0K
Followers
108.6K
Followers
15.5K
Followers
83.9K
Votes
3.8K
Votes
540
Votes
3.6K
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
  • 139
    Reliable and easy to use
  • 101
    High performance
  • 95
    Great with .net
  • 65
    Works well with .net
  • 56
    Easy to maintain
Cons
  • 4
    Expensive Licensing
  • 2
    Microsoft
  • 1
    Data pages is only 8k
  • 1
    The maximum number of connections is only 14000 connect
  • 1
    Replication can loose the data
Pros
  • 765
    Relational database
  • 511
    High availability
  • 439
    Enterprise class database
  • 383
    Sql
  • 304
    Sql + nosql
Cons
  • 10
    Table/index bloatings

What are some alternatives to MySQL, Microsoft SQL Server, PostgreSQL?

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.

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.

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.

Oracle

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.

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