Explore the Data Orchestration Stack—comprising Apache Airflow, Prefect, and Dagster—for building, scheduling, and monitoring modern data pipelines. This open-source stack provides unmatched flexibility, scalability, and reliability for data engineering teams. Discover the core libraries, integrations, and ecosystem tools that make this stack the industry standard for orchestrating ETL, batch, and machine learning workflows.
feature.delivery is a free, web-based platform that enables developers to monitor and consolidate software releases from multiple GitHub repositories into a single, streamlined chronological view. By centralizing release information across various tools, libraries, and services, feature.delivery simplifies the process of staying informed about the latest updates in a development stack. Stay ahead of the curve with feature.delivery, the free online tool designed to help developers effortlessly track and consolidate the latest releases from multiple GitHub repositories in one clean, chronological view. Whether you're managing a complex development stack or simply want to stay up to date with your favorite open-source projects, feature.delivery streamlines release tracking so you never miss an important update. By keeping up with the latest changes, developers can quickly adopt new features, enhance performance, and maintain a competitive edge in today's fast-moving tech landscape. Say goodbye to manual tracking and hello to smarter, faster development with feature.delivery.

https://feature.delivery

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PrefectHQ/
prefect

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airbytehq/
airbyte

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apache/
airflow

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apache/
airflow

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apache/
superset

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awslabs/
deequ

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celery/
celery

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dagster-io/
dagster

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dask/
dask

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grafana/
grafana

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great-expectations/
great_expectations

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hashicorp/
terraform

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helm/
helm

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kubernetes/
kubernetes

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meltano/
meltano

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open-telemetry/
opentelemetry-python

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prometheus/
prometheus

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singer-io/
getting-started

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streamlit/
streamlit

Use this link to track latest updates across the 19 repositories in Data Orchestration Stack

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how to keep up with the latest features in Data Orchestration Stack?
what's new in Data Orchestration Stack?
how to track latest features in Data Orchestration Stack?

Staying up-to-date with latest features of the
Data Orchestration Stack in 2026

How does it work?

feature.delivery is a free, web-based platform that helps developers track the latest releases from multiple GitHub repositories — all in one streamlined, chronological view. By centralizing release information across tools, libraries, and frameworks, feature.delivery makes it easier than ever to stay on top of the updates throughout your development stack.

Checkout this 1 minute intro video to see it in action

The Data Orchestration Stack (Apache Airflow, Prefect, Dagster) streamlines, automates, and manages complex data workflows for modern data engineering and analytics teams. Leveraging these open-source frameworks enables organizations to reliably schedule, monitor, and scale their data pipelines, ensuring data consistency, improved productivity, and operational excellence. The stack integrates seamlessly with a wide range of data sources and cloud services, empowering teams to build robust data platforms with ease.

Here's a breakdown of the Data Orchestration Stack into different categories

Core Orchestration Libraries

Core orchestration libraries are the backbone of the Data Orchestration Stack. They provide the foundational features for authoring, scheduling, and monitoring workflows and DAGs (Directed Acyclic Graphs).

Apache Airflow

apache/airflow
Platform to programmatically author, schedule, and monitor workflows.
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Prefect

PrefectHQ/prefect
Dataflow automation platform for building, running, and monitoring data pipelines.
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Dagster

dagster-io/dagster
An orchestration platform for the development, production, and observation of data assets.
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Task Execution & Scheduling

These libraries and plugins focus on advanced task execution, scheduling strategies, and scalability for high-throughput data workflows.

Celery

celery/celery
Distributed task queue for real-time and scheduled jobs, often used as an Airflow executor.
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Kubernetes Executor for Airflow

apache/airflow/tree/main/airflow/executors/kubernetes_executor.py
Native Kubernetes operator and executor for running Airflow tasks as pods.
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Dask

dask/dask
Parallel computing library used for scalable task execution in Prefect and Dagster.
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Data Integration & Connectors

Integrations and connectors facilitate seamless data ingestion, transformation, and output across varied data sources and sinks.

Airbyte

airbytehq/airbyte
Open-source ELT platform with hundreds of data connectors for source and destination systems.
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Singer

singer-io/getting-started
Open standard for writing scripts that move data between databases, web APIs, files, and more.
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Meltano

meltano/meltano
Data integration platform built on Singer for ELT pipelines and orchestration.
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new features in Meltano?

Monitoring & Observability

Monitoring and observability tools provide real-time tracking, logging, metrics, and alerting for data workflows, ensuring reliability and transparency.

Prometheus

prometheus/prometheus
Monitoring and alerting toolkit, widely used for metrics collection in orchestration stacks.
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Grafana

grafana/grafana
Open-source analytics and interactive visualization web application for monitoring metrics.
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OpenTelemetry

open-telemetry/opentelemetry-python
Toolkit for collecting distributed traces and metrics, integrating with orchestration platforms.
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Data Validation & Quality

Libraries in this category focus on data validation, pipeline testing, and ensuring the quality and reliability of data flowing through orchestrated workflows.

Great Expectations

great-expectations/great_expectations
Open-source platform for validating, documenting, and profiling data.
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Deequ

awslabs/deequ
Library for defining 'unit tests' for data, measuring and tracking data quality.
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Workflow UI & Visualization

User interfaces and visualization tools make it easier to design, debug, and monitor complex data workflows.

superset

apache/superset
Open-source data exploration and visualization platform, often integrated with orchestration stacks.
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Streamlit

streamlit/streamlit
Turns data scripts into shareable web apps, great for visualizing pipeline results.
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new features in Streamlit?

Infrastructure & Deployment

These tools manage the deployment, scaling, and infrastructure configuration for the orchestration stack, ensuring reliability and scalability.

Kubernetes

kubernetes/kubernetes
Container orchestration system for automating application deployment, scaling, and management.
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Helm

helm/helm
Kubernetes package manager for deploying orchestration stacks and their dependencies.
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Terraform

hashicorp/terraform
Infrastructure as Code (IaC) tool for provisioning cloud resources for orchestration stacks.
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Explore these open-source GitHub repositories to stay ahead with the latest releases and innovations in the Data Orchestration Stack. Click on the repository URLs to dive deeper into features, updates, and community contributions that power the most reliable and scalable data workflow platforms.