MySQL vs Postgresql vs Microsoft SQL Server Management Tools | Which Option is Best?

There are a lot of different SQL Management Tool options to choose from, but which one is right for you? In this video we take a high level look at the similarities and differences.

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0:00 Intro
1:14 High Level Comparison
3:44 MySQL User Interface and Features
5:43 Microsoft SQL Server User Interface and Features
10:08 Postgresql User Interface and Features
12:55 Overall Thoughts and Recommendations

[AlexTheAnalyst]

Thank you for everyone's feedback on this video. The intention of this video was to compare the UI and management tools for each of these, but the title and thumbnail was not representative of that. I updated the title and thumbnail to reflect it better. I do plan on diving into the actual databases to look at things like scalability, speed, and more. Thank you again for your feedback!

[tonyshelver]

I have used all these, MS SQL Server and PostgreSQL extensively for decades, nearly all in large system / large data applications. MySQL has been used for small systems. Also used Oracle quite a bit, especially in the 90s.

Review mostly focuses on the DB front end tool, rather than the DB capabilities, so a very misleading title / blurb to the video.
There are multiple DB user tools, other than the standard ones supplied by the DB, including ones that work across multiple database types.
The front end is a factor, but should NOT be the driving choice when looking at DB systems, unless you are a rank beginner, or have very simple DB needs.

This review is NOT highlighting how to actually select the right database, as behind the toolset they offer very different capabilities.
For example, Postgres has unparalleled support for time series, sharding and geospatial systems. PostGIS is the most powerful and widely used GIS DB extension / capability available on any DB type.

PostgreSQL is ultra-extensible. The extension system is designed in from inception, and in addition to sharding, time series, and so on, also provides multiple database programming languages. In addition to pgplsql (the equivalent of MS SQL TransactSQL), you can program in Python, C/C++, and many others via suitable extensions.
The list of extensions to support various capabilities likely runs in the 100s, and includes adding in different indexing and datatype options.

MS SQL: I used this extensively as well. The big stand out here for me is Transact SQL. If you are doing complex, large data set manipulations, or are really locking down the database against misuse via the use of triggers, rules and so on (can do the same in Postgres), this can be a life saver.

MySQL: their procedure / procedural support is very young, and nowhere near as robust as MS SQL or Postgres. MySSQL mostly came out of the embedded / small system / front end developer space, and has grown from there, where both MS SQL and Postgres have large system DB roots. (See ORM mention below)

So, I would say, if you are a beginner / front end developer, who is not going to focus on the DB capability, and has a fairly standard requirements list. look at MariaDB (open source MySQL), but you may want to consider PostgreSQL depending on your target application environment. MS SQL is great, but not open source.

ORM: The other use case for MySQL is if you are using the DB behind an ORM (object relational mapper), where the DB is just a data repository. Then it really doesn't make a huge difference which DB you select, as they are mostly black boxes. You should choose the DB that your ORM supports best, and is cheapest to own / operate. Obviously issues such as reliability and performance are important, and here Posgres and MS SQL have decades of experience to show.


In our case, PostgreSQL was the only choice. Our application is heavily GIS (Geographical Information System) and time series focused, where we have to analyse 100s of thousands of records for a single transaction to provide the functionality we need. We also use pgplsql functions heavily for update and extract transactions as we have multiple front ends for the application.


MS SQL was tested but the GIS component proved to just be too slow and not nearly as robust / functional as PostGIS. MySQL just didn't have the functionality to any useful degree.
We could have used Oracle, but the costs were prohibitive....

[SoumenMittra]

There's very little comparison between the databases shown in this video. It would be better if you would show us how the databases excel one above the other in use cases. 80% of the video is comparison between MySQL Workbench vs SSMS vs PG Admin. These are actually tools to access these databases. You can access these databases with other tools like SQL Assistant. These are actually comparisons of tools not the actual database.

[wesargrow]

I learned SQL on Postgres and importing/exporting was frustrating if you got an error.
I really enjoyed seeing the comparison of these platforms. Good stuff!

[rudroroy]

PostgreSQL does have a SQL extension it's called pg/plsql, it's very powerful, in fact, PostgreSQL is much more advance than MySQL only drawback is administration it's not as easy as MySQL and MSSQL

[thomasnas]

The quotation marks in PostgreSQL are only needed for establishing names to columns which could collide with system key words - for example a column called "name". And using the Schema name before the table is only needed when you have duplicate table names. So in both cases it's not a "weakness" compared to other databases, but simple features that can be used given a necessary scenario. And in terms of interface, all these applications run on the actual database, having multiple options for each engine, so again, it's hard to say the least which is the "better option", when it's a matter of personal preference.

[marcoalfaroazofeifa]

Having to play with the 3. Nowadays I liking Postgress better. It was much better support to JSON and it provides a plethora of built-in functions for time series and others

[maksimluzin]

Well, you should compare the SQL language dialect differences, because some of the DB servers have the built-in programming language 'extensions' and they are really quite different. But the SQL language is quite standardized (by ISO, IEEE standard or something) and the difference between the SQL dialects is mostly the servers' built-in functions, like string or data values processing and some special language extensions which are using the specific features of each DB-server. For example, the MS SQL server is using the T-SQL (Transact-SQL) programming language extension, but the PostgreSQL is using the PL/pgSQL (Procedural Language/PostGres Structured Query Language) and the Oracle DB-servers are using the PL/SQL (Programming Language/SQL) extension. The PL-extensions are used for the server-based business logic programming, mostly, for writing stored procedures, user functions, triggers, packages, etc. So, in my opinion, you should compare the SQL language dialect differences, not the PL-extensions and not the IDEs (which is not a property of the SQL language itself).

[tonyshelver]

Open source: You are not mentioning MariaDB, which is the open source fork of MySQL, and is becoming the default available in most Linux repositories, rather than MySQL which isn't true open source.

[wilsonman]

MySQL is great but the best one is always gunna be the one your company uses... so Microsoft SQL server it is! 😂

[ashrulochansahoo]

Thanks @Alex for taking the liberty to explain the differences and similarities on different SQLs. Really informative. However, we don't choose what to use. It's the employer's choice.

[_seyifunmitan_]

Thank you Alex for the video. It was very timely as I had a bit of a confusion stint yesterday when I was practicing on a website.

[justogonzalez]

Thank you Alex for keeping it direct and easy to understand. I worked for more than 20 years as a software developer since Turbo Pascal, Delphi, Visual Basic, Java, SQL, and after 8 years I'm getting updated to come back programming. Thank you for these videos.

[ChrisJarzynka]

Excellent comparison video - thank you!!! I used MongoDB (NoSQL) for a project because I wanted to be able to store ragged data formats for program preferences that wouldn't form neatly into a row/column table. I have since migrated to PostgreSQL since it has support for JSON and JSONB types which are even "indexable". Another big reason I went to Mongo was its ability to index spatial data (maps). Given Postgres's tight integration with mapping using PostGIS, it makes it a no-brainer for any map based database usage. BTW, I can't stand PG Admin, either when it was a compiled Windows/Mac program or now as a web based solution. It's slow and painful to use. I found a great multi-use SQL client, DBeaver, which in the free/community version supports many SQL versions and is lightning fast! Note: I have no relationship whatsoever to DBeaver - just found it, starting using it and became a huge fan!

[peterc]

Quoted column names are also required in Oracle if the column names are mixed case. To avoid having to quote all required names in queries I always capitalise on import of data.

[andregaspar]

I was just waiting you making a video about that! Thanks!

[robertbugna]

Thanks Alex! I used MySQL in my earlier years and totally agree with your points here :)

[CoreyThompson]

PostgreSQL is usually pronounced "post gress" and if you included the QL, you say " Q L" at the end, but since Postgres can also be a NoSQL DB (key pairs, JSON document storage, etc.), most people who use it regularly call it just Postgres..

[AljIsHere]

Ironically enough the MySQL in Steps book is the main one I am currently learning. It hasn't had any steps on learning how to import databases in the book. But that is ok. though. I do find it easier to learn. But I am going to go through the SQL Server one to understand the fundamentals too.

[GarthVader]

This is really helpful for me as I am studying and trying to get in the analytics field, knowing which to focus on is really useful. Thanks Alex.