Herramientas de pipelines de datos ELT
Software de código abierto para extraer datos sin procesar y realizar transformaciones directamente dentro de tu almacén de datos en la nube.
Herramientas de pipelines de datos ELT
Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
- airbytehq/airbyte
airbytehq/airbyte
21,472Ver en GitHubAirbyte is a data integration platform designed to synchronize information between diverse applications, databases, and data warehouses. It functions as an extract, transform, and load orchestrator that manages automated data movement workflows across cloud, on-premise, and hybrid environments. The platform provides a standardized interface for connectors, enabling the movement of structured and unstructured data while maintaining stateful checkpoints for reliable incremental syncing. The platform distinguishes itself through a containerized architecture that isolates connectors to prevent de
Airbyte is a data integration platform that extracts data from many sources, loads it raw into data warehouses, and can apply transformations within the warehouse via its normalization layer or dbt integration, making it a flagship ELT tool that addresses all the key requirements you listed.
PythonSchema Evolution - meltano/meltano
meltano/meltano
2,534Ver en GitHubMeltano is an open-source platform for building, running, and orchestrating ELT (Extract, Load, Transform) data pipelines. It provides a declarative, YAML-driven configuration system that defines entire pipeline workflows, including data connectors, schedules, and transformations, without requiring imperative code. The platform is built on the Singer specification for data connectors and integrates with dbt for SQL-based transformations and Apache Airflow for scheduling and orchestration. What distinguishes Meltano is its comprehensive approach to pipeline management, combining a curated cata
Meltano is a purpose-built open-source ELT platform that uses Singer connectors for extraction and dbt for SQL-based transformations inside the warehouse, with built-in orchestration via Airflow—exactly matching the ELT paradigm and covering the required features like source connectors, incremental loading, and multi-warehouse support.
PythonBusiness IntelligenceData IntegrationData Pipelines and Orchestration
