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

dbt

316
311
+ 1
6
Looker

480
525
+ 1
9
Add tool
Decisions about dbt and Looker

Very easy-to-use UI. Good way to make data available inside the company for analysis.

Has some built-in visualizations and can be easily integrated with other JS visualization libraries such as D3.

Can be embedded into product to provide reporting functions.

Support team are helpful.

The only complain I have is lack of API support. Hard to track changes as codes and automate report deployment.

See more
Vojtech Kopal
Head of Data at Mews Systems | 3 upvotes 路 217.3K views

Power BI is really easy to start with. If you have just several Excel sheets or CSV files, or you build your first automated pipeline, it is actually quite intuitive to build your first reports.

And as we have kept growing, all the additional features and tools were just there within the Azure platform and/or Office 365.

Since we started building Mews, we have already passed several milestones in becoming start up, later also a scale up company and now getting ready to grow even further, and during all these phases Power BI was just the right tool for us.

See more
Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn More
Pros of dbt
Pros of Looker
  • 1
    Easy for SQL programmers to learn
  • 1
    Modularity, portability, CI/CD, and documentation
  • 1
    Faster Integrated Testing
  • 1
    Reusable Macro
  • 1
    Schedule Jobs
  • 1
    CI/CD
  • 4
    Real time in app customer chat support
  • 4
    GitHub integration
  • 1
    Reduces the barrier of entry to utilizing data

Sign up to add or upvote prosMake informed product decisions

Cons of dbt
Cons of Looker
    Be the first to leave a con
    • 2
      Price

    Sign up to add or upvote consMake informed product decisions

    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 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.

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

    Jobs that mention dbt and Looker as a desired skillset
    CBRE
    United Kingdom of Great Britain and Northern Ireland England Basildon
    CBRE
    United Kingdom of Great Britain and Northern Ireland England London
    CBRE
    United States of America Nebraska Springfield
    CBRE
    United States of America Virginia Sandston
    CBRE
    Poland Mazowieckie Warsaw
    CBRE
    Netherlands Noord-Holland Amsterdam
    CBRE
    Netherlands Noord-Holland Amsterdam
    What companies use dbt?
    What companies use Looker?
    See which teams inside your own company are using dbt or Looker.
    Sign up for StackShare EnterpriseLearn More

    Sign up to get full access to all the companiesMake informed product decisions

    What tools integrate with dbt?
    What tools integrate with Looker?

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

    Blog Posts

    What are some alternatives to dbt and Looker?
    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.
    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.
    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