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Prefect is a workflow orchestration platform designed to define, schedule, and monitor complex data pipelines as Python code. It functions as a container-native engine that wraps individual tasks in isolated environments, ensuring consistent dependencies and resource allocation across diverse infrastructure. By utilizing a state-machine-based orchestration model, the system tracks execution progress through discrete transitions and persistent event logs to maintain reliable and observable task processing. The platform distinguishes itself through a decoupled worker-API architecture, which sep
Orchest is a data pipeline orchestrator and containerized workflow manager. It provides a platform for designing, scheduling, and executing complex data processing sequences through a combination of a graphical interface and scripting. The platform distinguishes itself by using containers to manage software dependencies, ensuring consistent execution across different environments. It features a polyglot task scheduler capable of triggering jobs written in multiple programming languages and includes a version control system that tracks historical snapshots of project configurations and code.
Metaflow is a Python machine learning framework and MLOps workflow orchestrator designed to manage the lifecycle of data pipelines from local prototyping to production. It serves as a distributed compute manager and an experiment tracking system, enabling the creation of reproducible pipelines that transition between development and high-availability production environments. The framework distinguishes itself through an integrated checkpointing system that automatically persists intermediate data artifacts to remote storage, allowing failed runs to be resumed from the last successful step. It
Unified Interface for Constructing and Managing Workflows on different workflow engines, such as Argo Workflows, Tekton Pipelines, and Apache Airflow.
The fastest ⚡️ way to build data pipelines. Develop iteratively, deploy anywhere. ☁️
The main features of ploomber/ploomber are: ML Ops, Workflow Orchestration, Data Pipelines, Data Orchestration, GitOps And Continuous Delivery, Interactive Notebooks, Publishing and Conversion.
Open-source alternatives to ploomber/ploomber include: orchest/orchest — Orchest is a data pipeline orchestrator and containerized workflow manager. It provides a platform for designing,… prefecthq/prefect — Prefect is a workflow orchestration platform designed to define, schedule, and monitor complex data pipelines as… dagster-io/dagster — Dagster is a data orchestration platform designed to manage the entire lifecycle of data assets through declarative… netflix/metaflow — Metaflow is a Python machine learning framework and MLOps workflow orchestrator designed to manage the lifecycle of… couler-proj/couler — Unified Interface for Constructing and Managing Workflows on different workflow engines, such as Argo Workflows,… argoproj/argo-workflows — Argo Workflows is a container-native workflow engine that functions as a Kubernetes custom resource controller. It…