Etl Framework
Showing 12 of 12 projects
A server-side data processing pipeline that ingests, transforms, and ships logs and events from multiple sources.
An ultra-performant data transformation framework for AI, with incremental processing and data lineage built-in.
Open-source data pipelines to sync cloud infrastructure metadata from AWS, Azure, GCP, and 70+ sources into your data warehouse.
Open-source data pipelines for cloud asset inventory, CSPM, FinOps, and vulnerability management across AWS, Azure, GCP, and 70+ sources.
A Python library for defining portable, modular, and testable data transformation DAGs with built-in lineage and metadata.
A lightweight Python library for creating portable, expressive, and testable data transformation DAGs with built-in lineage and metadata.
A distributed data integration framework for big data ecosystems, handling ingestion, replication, organization, and lifecycle management for both streaming and batch data.
Definition and SQL DDLs for the OMOP Common Data Model, enabling standardized observational health data.
A simple, fast, and flexible ETL framework for .NET with built-in readers and writers for CSV, JSON, XML, Parquet, and more.
A lightweight ETL library and data integration toolbox for .NET, enabling programmatic data flow pipelines.
A stream processing platform with a pluggable architecture for connecting data feeds to transformation operators.
A lightweight Node.js ETL framework for extracting data from databases and loading it into data lakes and warehouses.
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