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dbt vs Sequel Pro: What are the differences?

dbt: A command line tool that enables data analysts and engineers to transform data in their warehouse more effectively. dbt - Documentation; Sequel Pro: MySQL database management for Mac OS X. Sequel Pro is a fast, easy-to-use Mac database management application for working with MySQL databases.

dbt and Sequel Pro can be categorized as "Database" tools.

Sequel Pro is an open source tool with 6.73K GitHub stars and 591 GitHub forks. Here's a link to Sequel Pro's open source repository on GitHub.

Movielala, Algorithmia, and Nano Solutions are some of the popular companies that use Sequel Pro, whereas dbt is used by nurx, Trussle, and Flux Work. Sequel Pro has a broader approval, being mentioned in 46 company stacks & 23 developers stacks; compared to dbt, which is listed in 3 company stacks and 4 developer stacks.

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Pros of dbt
Pros of Sequel Pro
  • 1
    Easy for SQL programmers to learn
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  • 18
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    Clean UI
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What is dbt?

It enables analytics engineers to transform data in their warehouses by simply writing select statements. It handles turning these select statements into tables and views.

What is Sequel Pro?



What companies use dbt?
What companies use Sequel Pro?
See which teams inside your own company are using dbt or Sequel Pro.
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What tools integrate with dbt?
What tools integrate with Sequel Pro?
What are some alternatives to dbt and Sequel Pro?
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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.
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.
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.
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