dbt vs Microsoft SQL Server Management Studio

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Microsoft SQL Server Management Studio vs dbt: What are the differences?

Introduction This Markdown code provides a comparison between Microsoft SQL Server Management Studio (SSMS) and dbt, outlining the key differences between the two tools.

  1. Connectivity and Platform Compatibility: Microsoft SSMS is primarily designed for managing Microsoft SQL Server databases, offering seamless connectivity and optimal support for Microsoft's platforms. On the other hand, dbt is a tool that works with various types of databases, including Redshift, Snowflake, and BigQuery, providing versatility and platform compatibility.

  2. Data Transformation and Modeling: SSMS offers robust data transformation capabilities through T-SQL scripting and SQL Server Integration Services (SSIS). It provides a comprehensive platform for modeling and managing data. In comparison, dbt focuses primarily on data transformation, modeling, and orchestrating complex SQL workflows. It is specifically designed for data analytics and enables version control, testing, and documentation of data models.

  3. Version Control and Collaboration: SSMS lacks built-in version control capabilities, making it challenging for teams to collaborate effectively. On the other hand, dbt natively integrates with version control systems like Git, enabling seamless collaboration, code reviews, and maintaining a centralized repository for managing data transformations.

  4. Code Reusability and Modularization: SSMS relies heavily on stored procedures, which can be reused across different projects. However, the reusability is limited to SQL code only. In contrast, dbt promotes code reusability and modularization by allowing the creation of SQL "macros." These macros can be shared across projects, promoting consistency and efficiency in data transformations.

  5. Testing and Documentation: SSMS lacks native testing frameworks and tools for data validation and quality assurance. In contrast, dbt provides built-in testing capabilities, allowing developers to define and execute tests on data transformations, ensuring the correctness of the output. Additionally, dbt generates documentation automatically, making it easier to understand and maintain data models.

  6. Data Pipeline Orchestration: SSMS does not provide built-in features for orchestrating data pipelines, making it challenging to manage complex data workflows. Conversely, dbt offers powerful orchestration capabilities, allowing users to define and schedule complex data transformations and dependencies, ensuring data pipelines run efficiently and reliably.

In summary, Microsoft SQL Server Management Studio is a comprehensive database management tool primarily designed for Microsoft SQL Server, while dbt is a data transformation and modeling tool that offers platform compatibility, collaborative features, code reusability, testing capabilities, and data pipeline orchestration.

Advice on dbt and Microsoft SQL Server Management Studio

I am looking to build an azure database that connects to my power bi application. Initially, I attempted to create an Azure SQL database, then realized I needed to have SQL Server Management Service in order to manage and connect between Azure SQL <=> Power BI, but since I am on a Mac, I had to use the complex installation as a workaround.

If MySQL Workbench can solve this (as the product is available on Mac), I am more than happy to proceed with this approach if it can achieve the same goal of connecting an azure database with my Power BI application

What I am trying to achieve is fairly simple: have an online cloud database that connects to my Power BI application

I am open to any other solutions as well

Thank you

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Replies (5)
Oded Arbel
Recommends
on
MySQL WorkBenchMySQL WorkBench

As others have noted, MySQL Workbench cannot be used instead of Microsoft SQL Manager to manage Azure SQL (MS-SQL Server, I hate that Microsoft uses generic category names for their products).

If you're considering switching to MySQL (Possibly using Azure MySQL managed database), then please not that unlike MS-SQL Server, you do not need the MySQL Workbench to connect your application to MysQL: just use the correct driver for your stack, and you're all set (if your stack is using the .Net platform, use MySQL Connector/NET from: https://dev.mysql.com/downloads/connector/net/ ).

If you do want to use a graphical interface to maintain your MySQL database, then MySQL Workbench is a great choice, but you are not limited to it - as others have mentioned, there is a plethora of competing graphical database management tools that would work just as well with MySQL - one of the advantages of choosing MySQL for your stack is the huge eco-system that is built around it.

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Lawrence Fernandes
Data Engineer at B2W Digital · | 1 upvotes · 191.3K views
Recommends
on
DBeaverDBeaver

Hello Could you give us a better idea of what Data Base Management System (DBMS) you are using at Azure? MySQL Workbench and Microsoft SQL Server Management Studio (SSMS) are tools developed to exclusively manage MySQL and SQL Server, respectively. If you need to manage multiple DBMS's from a single tool, I sugget you try DBeaver. There are also another alternatives: HeidiSQL, phpMyAdmin, etc. Regarding the DBMS itself, I suggest you stick with SQL Server. In my opinion it's more stable and has more features than MySQL - especially in the Standard and Enterprise editions. Regards, Lawrence

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Povilas Brilius
PHP Web Developer at GroundIn Software · | 1 upvotes · 191.7K views

As far as I know, MySQL Workbench doesn't handle Microsoft connections, including Azure, you should try Microsoft solutions such as MS VS Code.

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Julien DeFrance
Principal Software Engineer at Tophatter · | 1 upvotes · 191.2K views

Hi Aashwiin, Looking at your stack (https://stackshare.io/aashwiin82347/my-stack), it seems you are using Azure SQL Databases. I'll infer this is Microsoft SQL Server. Therefore, it certainly makes sense you stick with some of the official Microsoft Tooling to connect to it, query and administer it. You'd only be looking at MySQL Query Workbench, if you were running and connecting to a MySQL Database. - That said, could Azure MySQL (https://docs.microsoft.com/en-us/azure/mysql/overview) be an option for you a this point? MySQL offers great performance. I have been running it at various companies (under AWS/RDS and AWS/Aurora) and have no reason to switch over to anything else. - Decision making-wise, how much do your want your local sql/mysql client to influence/weigh in your architecture/technology decisions, though? This can be a slippery slope. - Alternatively, other clients exist, such as "Table Plus" and allow you to connect, on Mac, to a variety of database servers, including SQL Server. It might be worth giving it a try.

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Erica Rowe
Tech Lead at eComEngine LLC · | 1 upvotes · 191.3K views
Recommends
on
AzureDataStudioAzureDataStudio

Microsoft provides an application known as Azure Data Studio that runs on Windows, Mac and Linux machines. It provides the ability to manage an Azure SQL database, as well as connecting to standard SQL Server databases. https://docs.microsoft.com/en-us/sql/azure-data-studio/what-is?view=sql-server-ver15

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Pros of dbt
Pros of Microsoft SQL Server Management Studio
  • 5
    Easy for SQL programmers to learn
  • 2
    CI/CD
  • 2
    Schedule Jobs
  • 2
    Reusable Macro
  • 2
    Faster Integrated Testing
  • 2
    Modularity, portability, CI/CD, and documentation
    Be the first to leave a pro

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    Cons of dbt
    Cons of Microsoft SQL Server Management Studio
    • 1
      Only limited to SQL
    • 1
      Cant do complex iterations , list comprehensions etc .
    • 1
      People will have have only sql skill set at the end
    • 1
      Very bad for people from learning perspective
      Be the first to leave a con

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      What is dbt?

      dbt is a transformation workflow that lets teams deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documentation. Now anyone who knows SQL can build production-grade data pipelines.

      What is Microsoft SQL Server Management Studio?

      It is an integrated environment for managing any SQL infrastructure, from SQL Server to Azure SQL Database. It provides tools to configure, monitor, and administer instances of SQL Server and databases. Use it to deploy, monitor, and upgrade the data-tier components used by your applications, as well as build queries and scripts.

      Need advice about which tool to choose?Ask the StackShare community!

      What companies use dbt?
      What companies use Microsoft SQL Server Management Studio?
      See which teams inside your own company are using dbt or Microsoft SQL Server Management Studio.
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      Sign up to get full access to all the companiesMake informed product decisions

      What tools integrate with dbt?
      What tools integrate with Microsoft SQL Server Management Studio?

      Sign up to get full access to all the tool integrationsMake informed product decisions

      What are some alternatives to dbt and Microsoft SQL Server Management Studio?
      act
      Rather than having to commit/push every time you want test out the changes you are making to your .github/workflows/ files (or for any changes to embedded GitHub actions), you can use this tool to run the actions locally. The environment variables and filesystem are all configured to match what GitHub provides.
      Airflow
      Use Airflow to author workflows as directed acyclic graphs (DAGs) of tasks. The Airflow scheduler executes your tasks on an array of workers while following the specified dependencies. Rich command lines utilities makes performing complex surgeries on DAGs a snap. The rich user interface makes it easy to visualize pipelines running in production, monitor progress and troubleshoot issues when needed.
      Looker
      We've built a unique data modeling language, connections to today's fastest analytical databases, and a service that you can deploy on any infrastructure, and explore on any device. Plus, we'll help you every step of the way.
      Apache Spark
      Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
      Slick
      It is a modern database query and access library for Scala. It allows you to work with stored data almost as if you were using Scala collections while at the same time giving you full control over when a database access happens and which data is transferred.
      See all alternatives