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dbt

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Spring Data

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+ 1

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dbt vs Spring Data: What are the differences?

What is dbt? A command line tool that enables data analysts and engineers to transform data in their warehouse more effectively. dbt - Documentation.

What is Spring Data? Provides a consistent approach to data access – relational, non-relational, map-reduce, and beyond. 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.

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

Spring Data is an open source tool with 56 GitHub stars and 62 GitHub forks. Here's a link to Spring Data's open source repository on GitHub.

Monkey Exchange, Hocelot, and apside are some of the popular companies that use Spring Data, whereas dbt is used by nurx, Trussle, and Flux Work. Spring Data has a broader approval, being mentioned in 10 company stacks & 10 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 Spring Data

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

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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 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.

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Jobs that mention dbt and Spring Data as a desired skillset

Technical Manager - Data Centre Solutions

CBRE

United Kingdom of Great Britain and Northern Ireland England Basildon

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Data Center M&E Shift Manager - Heathrow

CBRE

United Kingdom of Great Britain and Northern Ireland England London

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Data Entry Coordinator

CBRE

United States of America Nebraska Springfield

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Data Entry Coordinator

CBRE

United States of America Virginia Sandston

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Quality Engineer

CBRE

Poland Mazowieckie Warsaw

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DataCenter M&E Technician

CBRE

Netherlands Noord-Holland Amsterdam

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Junior Finance Analyst

CBRE

Netherlands Noord-Holland Amsterdam

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Senior Software Engineer/Lead

CBRE

Poland Mazowieckie Warsaw

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+16

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What companies use dbt?

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What are some alternatives to dbt and Spring Data?

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.

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dbt vs Spring Data

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Pros of dbt

Pros of Spring Data

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What is dbt?

What is Spring Data?

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

What companies use dbt?

What companies use Spring Data?

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What tools integrate with dbt?

What tools integrate with Spring Data?

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

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