¿Cuáles son las características principales de bruin-data/bruin?

Las características principales de bruin-data/bruin son: Data Ingestion, Data Ingestion Pipelines, Data Integration Providers, Data Orchestration, Data Pipelines, Workflow Orchestration, CI/CD and Orchestration.

Bruin - build and test data pipelines

Name: bruin-data/bruin
Author: bruin-data

Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows.

Features

Data Ingestion - End-to-end pipeline tool for ingestion, transformation, and quality.
Data Ingestion Pipelines - End-to-end pipeline tool for ingestion and quality checks.
Data Integration Providers - Layer for data ingestion and transformation across multiple sources.
Data Orchestration - Data pipeline framework supporting SQL and Python DAGs.
Data Pipelines - End-to-end pipeline tool for ingestion and transformation.
Workflow Orchestration - CLI tool for end-to-end pipeline management and data quality.
CI/CD and Orchestration - Run and schedule SQL transformations without Airflow.

Historial de estrellas

Build data pipelines with SQL and Python, ingest data from different sources, add quality checks, and build end-to-end flows.

Features

Data Ingestion - End-to-end pipeline tool for ingestion, transformation, and quality.
Data Ingestion Pipelines - End-to-end pipeline tool for ingestion and quality checks.
Data Integration Providers - Layer for data ingestion and transformation across multiple sources.
Data Orchestration - Data pipeline framework supporting SQL and Python DAGs.
Data Pipelines - End-to-end pipeline tool for ingestion and transformation.
Workflow Orchestration - CLI tool for end-to-end pipeline management and data quality.
CI/CD and Orchestration - Run and schedule SQL transformations without Airflow.

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Historial de estrellas

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