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dbt vs Liquibase: 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; Liquibase: Source control for your database. Developers store database changes in text-based files on their local development machines and apply them to their local databases. Changelog files can be be arbitrarily nested for better management.

dbt and Liquibase belong to "Database Tools" category of the tech stack.

Liquibase is an open source tool with 1.78K GitHub stars and 1.09K GitHub forks. Here's a link to Liquibase's open source repository on GitHub.

Viadeo, Orbitz, and Virgin Pulse are some of the popular companies that use Liquibase, whereas dbt is used by nurx, Trussle, and Flux Work. Liquibase has a broader approval, being mentioned in 15 company stacks & 12 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 Liquibase
  • 1
    Easy for SQL programmers to learn
  • 17
    Great database tool
  • 14
    Many DBs supported
  • 9
    Easy setup
  • 6
    Database independent migration scripts
  • 3
    Database version controller
  • 3
    Unique open source tool
  • 1
    Supports NoSQL and Graph DBs

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Cons of dbt
Cons of Liquibase
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    • 3
      No vendor specifics in XML format - needs workarounds
    • 3
      Documentation is disorganized

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    - No public GitHub repository available -

    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 Liquibase?

    Liquibase is a leading open-source tool for database schema change management. Liquibase helps teams track, version, and deploy database schema and logic changes so they can automate their database code process with their app code process.

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    What companies use dbt?
    What companies use Liquibase?
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    What tools integrate with dbt?
    What tools integrate with Liquibase?

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    What are some alternatives to dbt and Liquibase?
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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.
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    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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