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dbt

456
426
+ 1
15
Slick

9.2K
1.2K
+ 1
0
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dbt vs Slick: 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; Slick: Database query and access library for Scala. 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.

dbt and Slick can be categorized as "Database" tools.

Slick is an open source tool with 2.27K GitHub stars and 542 GitHub forks. Here's a link to Slick's open source repository on GitHub.

orat.io, Massdrop, and SpringRole are some of the popular companies that use Slick, whereas dbt is used by nurx, Trussle, and Flux Work. Slick has a broader approval, being mentioned in 7789 company stacks & 4 developers stacks; compared to dbt, which is listed in 4 company stacks and 8 developer stacks.

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Pros of dbt
Pros of Slick
  • 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
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    Cons of dbt
    Cons of Slick
    • 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
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      - No public GitHub repository available -

      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 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.

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

      What companies use dbt?
      What companies use Slick?
      See which teams inside your own company are using dbt or Slick.
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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 Slick?

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      What are some alternatives to dbt and Slick?
      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.
      Spring Data
      It makes it easy to use data access technologies, relational and non-relational databases, map-reduce frameworks, and cloud-based data services. This is an umbrella project which contains many subprojects that are specific to a given database.
      See all alternatives