Explore the Data Pipeline Stack, featuring Apache Airflow, Apache NiFi, and AWS Glue, to streamline your data engineering workflows. This stack offers powerful scheduling, orchestration, and ETL capabilities, backed by a rich ecosystem of open-source tools and libraries. Learn about the essential components and repositories that make this stack a top choice for scalable and reliable data pipelines.
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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ClickHouse/
ClickHouse

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PrefectHQ/
prefect

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airbytehq/
airbyte

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apache/
airflow

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apache/
beam

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apache/
camel

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apache/
nifi

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apache/
superset

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astronomer/
airflow-provider-great-expectations

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aws/
aws-glue-samples

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dagster-io/
dagster

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dbt-labs/
dbt-core

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delta-io/
delta

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duckdb/
duckdb

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great-expectations/
great_expectations

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pandas-dev/
pandas

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prometheus/
prometheus

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singer-io/
getting-started

Use this link to track latest updates across the 18 repositories in Data Pipeline Stack

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how to keep up with the latest features in Data Pipeline Stack?
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how to track latest features in Data Pipeline Stack?

Staying up-to-date with latest features of the
Data Pipeline 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 Pipeline Stack (Apache Airflow, Apache NiFi, AWS Glue) empowers organizations to design, schedule, orchestrate, and monitor complex data workflows efficiently. Leveraging open-source tools, this stack enables robust data ingestion, transformation, and integration, facilitating scalable, reliable, and automated data pipelines. With community-driven innovation, extensibility, and seamless integration with cloud and on-premises environments, this stack is ideal for modern data engineering and analytics.

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

Core Orchestration Libraries

These repositories form the backbone of the Data Pipeline Stack, providing workflow scheduling, orchestration, and management capabilities. They empower users to automate complex data flows and ensure data reliability and consistency.

Apache Airflow

apache/airflow
A platform to programmatically author, schedule, and monitor workflows.
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Apache NiFi

apache/nifi
An easy-to-use, powerful, and reliable system to process and distribute data.
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AWS Glue

aws/aws-glue-samples
A serverless data integration service that makes it easy to discover, prepare, and combine data.
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Data Connectors and Integrations

These repositories extend the stack's capabilities, allowing connectivity to disparate data sources and sinks. They are crucial for integrating databases, cloud storage, and third-party platforms into your pipelines.

Airbyte

airbytehq/airbyte
Open-source data integration platform for ELT pipelines, with a wide range of connectors.
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Singer

singer-io/getting-started
A standard for writing scripts that move data, and a collection of connectors called 'taps' and 'targets.'
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Apache Camel

apache/camel
Powerful integration framework based on enterprise integration patterns.
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Data Transformation & Processing

These libraries provide advanced tools for ETL (Extract, Transform, Load), data cleaning, and processing tasks. They enable complex data manipulations within pipelines for analytics and machine learning.

dbt (data build tool)

dbt-labs/dbt-core
Enables analytics engineers to transform data in their warehouse more effectively.
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new features in dbt (data build tool)?

Apache Beam

apache/beam
Unified programming model for batch and streaming data processing.
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pandas

pandas-dev/pandas
Powerful Python library for data manipulation and analysis.
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new features in pandas?

Monitoring & Observability

Monitoring tools are vital for ensuring pipeline health, tracking data lineage, and alerting on failures. They provide insights into pipeline performance and reliability.

Apache Superset

apache/superset
Modern data exploration and visualization platform.
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new features in Apache Superset?

Prometheus

prometheus/prometheus
Open-source systems monitoring and alerting toolkit.
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Great Expectations

great-expectations/great_expectations
Helps validate, document, and profile data to ensure data quality.
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Data Storage & Warehousing

These repositories support data persistence, warehousing, and scalable data storage for pipeline outputs and staging.

ClickHouse

ClickHouse/ClickHouse
Fast open-source OLAP database management system.
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new features in ClickHouse?

Delta Lake

delta-io/delta
Storage layer that brings ACID transactions to Apache Spark and big data workloads.
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DuckDB

duckdb/duckdb
In-process SQL OLAP database management system.
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new features in DuckDB?

Workflow Utilities & Extensions

This category includes plugins, operators, and extensions that enhance the capabilities of core pipeline orchestration tools.

astronomer/airflow-provider-great-expectations

astronomer/airflow-provider-great-expectations
Airflow Provider for Great Expectations, enabling data quality checks within Airflow DAGs.
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Prefect

PrefectHQ/prefect
Modern workflow orchestration for data-intensive 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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new features in dagster?

To stay up-to-date with the latest improvements, releases, and updates for the Data Pipeline Stack, explore the official repositories linked above. Click on each repository's URL to discover new features, community contributions, and detailed release notes that can help you optimize your data pipeline workflows.