dbt vs Open PostgreSQL Monitoring

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

dbt

370
368
+ 1
14
Open PostgreSQL Monitoring

177
145
+ 1
0
Add tool

dbt vs Open PostgreSQL Monitoring: What are the differences?

Developers describe dbt as "A command line tool that enables data analysts and engineers to transform data in their warehouse more effectively". dbt - Documentation. On the other hand, Open PostgreSQL Monitoring is detailed as "Oversee and Manage Your PostgreSQL Servers". Open PostgreSQL Monitoring is a free software designed to help you manage your PostgreSQL servers.

dbt and Open PostgreSQL Monitoring can be categorized as "Database" tools.

Open PostgreSQL Monitoring is an open source tool with 149 GitHub stars and 10 GitHub forks. Here's a link to Open PostgreSQL Monitoring's open source repository on GitHub.

According to the StackShare community, Open PostgreSQL Monitoring has a broader approval, being mentioned in 16 company stacks & 15 developers stacks; compared to dbt, which is listed in 3 company stacks and 4 developer stacks.

Get Advice from developers at your company using StackShare Enterprise. Sign up for StackShare Enterprise.
Learn More
Pros of dbt
Pros of Open PostgreSQL Monitoring
  • 4
    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

    Sign up to add or upvote prosMake informed product decisions

    Cons of dbt
    Cons of Open PostgreSQL Monitoring
    • 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

      Sign up to add or upvote consMake informed product decisions

      - 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 Open PostgreSQL Monitoring?

      Open PostgreSQL Monitoring is a free software designed to help you manage your PostgreSQL servers.

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

      Jobs that mention dbt and Open PostgreSQL Monitoring as a desired skillset
      CBRE
      United States of America Texas Richardson
      CBRE
      Netherlands Groningen Eemshaven
      CBRE
      Netherlands Noord-Holland Amsterdam
      CBRE
      Netherlands Groningen Eemshaven
      CBRE
      Netherlands Noord-Holland Amsterdam
      CBRE
      Netherlands Noord-Holland Amsterdam
      CBRE
      Netherlands Noord-Holland Amsterdam
      CBRE
      United States of America Texas Richardson
      What companies use dbt?
      What companies use Open PostgreSQL Monitoring?
      See which teams inside your own company are using dbt or Open PostgreSQL Monitoring.
      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 Open PostgreSQL Monitoring?

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

      What are some alternatives to dbt and Open PostgreSQL Monitoring?
      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