Apache AirflowThe Apache Software Foundation
|
DataBuckFirstEigen
|
|||||
About
Airflow is a platform created by the community to programmatically author, schedule and monitor workflows. Airflow has a modular architecture and uses a message queue to orchestrate an arbitrary number of workers. Airflow is ready to scale to infinity. Airflow pipelines are defined in Python, allowing for dynamic pipeline generation. This allows for writing code that instantiates pipelines dynamically. Easily define your own operators and extend libraries to fit the level of abstraction that suits your environment. Airflow pipelines are lean and explicit. Parametrization is built into its core using the powerful Jinja templating engine. No more command-line or XML black-magic! Use standard Python features to create your workflows, including date time formats for scheduling and loops to dynamically generate tasks. This allows you to maintain full flexibility when building your workflows.
|
About
DataBuck is an AI-powered data validation platform that automates risk detection across dynamic, high-volume, and evolving data environments. DataBuck empowers your teams to:
✅ Enhance trust in analytics and reports, ensuring they are built on accurate and reliable data.
✅ Reduce maintenance costs by minimizing manual intervention.
✅ Scale operations 10x faster compared to traditional tools, enabling seamless adaptability in ever-changing data ecosystems.
By proactively addressing system risks and improving data accuracy, DataBuck ensures your decision-making is driven by dependable insights.
Proudly recognized in Gartner’s 2024 Market Guide for #DataObservability, DataBuck goes beyond traditional observability practices with its AI/ML innovations to deliver autonomous Data Trustability—empowering you to lead with confidence in today’s data-driven world.
|
|||||
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
|
|||||
Audience
Anyone who wants to to programmatically author, schedule and monitor workflows
|
Audience
Data professionals interested in a powerful autonomous data quality validation platform
|
|||||
Support
Phone Support
24/7 Live Support
Online
|
Support
Phone Support
24/7 Live Support
Online
|
|||||
API
Offers API
|
API
Offers API
|
|||||
Screenshots and Videos |
Screenshots and Videos |
|||||
Pricing
No information available.
Free Version
Free Trial
|
Pricing
No information available.
Free Version
Free Trial
|
|||||
Reviews/
|
Reviews/
|
|||||
Training
Documentation
Webinars
Live Online
In Person
|
Training
Documentation
Webinars
Live Online
In Person
|
|||||
Company InformationThe Apache Software Foundation
Founded: 1999
United States
airflow.apache.org
|
Company InformationFirstEigen
Founded: 2015
United States
firsteigen.com/databuck/
|
|||||
Alternatives |
Alternatives |
|||||
|
|
||||||
|
|
|
|||||
|
|
||||||
Categories |
Categories |
|||||
Big Data Features
Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates
Data Quality Features
Address Validation
Data Deduplication
Data Discovery
Data Profililng
Master Data Management
Match & Merge
Metadata Management
|
||||||
Integrations
Amazon Web Services (AWS)
Cloudera
Coursebox AI
Dagster
DataBuck
Datafold
Great Expectations
IBM watsonx.data integration
Kedro
MaxPatrol
|
Integrations
Amazon Web Services (AWS)
Cloudera
Coursebox AI
Dagster
DataBuck
Datafold
Great Expectations
IBM watsonx.data integration
Kedro
MaxPatrol
|
|||||
|
|
