Average Ratings 0 Ratings
Average Ratings 6 Ratings
Description
Airflow is a community-driven platform designed for the programmatic creation, scheduling, and monitoring of workflows. With its modular architecture, Airflow employs a message queue to manage an unlimited number of workers, making it highly scalable. The system is capable of handling complex operations through its ability to define pipelines using Python, facilitating dynamic pipeline generation. This flexibility enables developers to write code that can create pipelines on the fly. Users can easily create custom operators and expand existing libraries, tailoring the abstraction level to meet their specific needs. The pipelines in Airflow are both concise and clear, with built-in parametrization supported by the robust Jinja templating engine. Eliminate the need for complex command-line operations or obscure XML configurations! Instead, leverage standard Python functionalities to construct workflows, incorporating date-time formats for scheduling and utilizing loops for the dynamic generation of tasks. This approach ensures that you retain complete freedom and adaptability when designing your workflows, allowing you to efficiently respond to changing requirements. Additionally, Airflow's user-friendly interface empowers teams to collaboratively refine and optimize their workflow processes.
Description
Big Data Quality must always be verified to ensure that data is safe, accurate, and complete. Data is moved through multiple IT platforms or stored in Data Lakes. The Big Data Challenge: Data often loses its trustworthiness because of (i) Undiscovered errors in incoming data (iii). Multiple data sources that get out-of-synchrony over time (iii). Structural changes to data in downstream processes not expected downstream and (iv) multiple IT platforms (Hadoop DW, Cloud). Unexpected errors can occur when data moves between systems, such as from a Data Warehouse to a Hadoop environment, NoSQL database, or the Cloud. Data can change unexpectedly due to poor processes, ad-hoc data policies, poor data storage and control, and lack of control over certain data sources (e.g., external providers). DataBuck is an autonomous, self-learning, Big Data Quality validation tool and Data Matching tool.
API Access
Has API
No
API Access
Has API
Yes
Integrations
Amazon Web Services (AWS)
No
Ardent
Yes
Azure SQL Database
No
Beats
Yes
BentoML
Yes
Cake AI
Yes
Google Cloud BigQuery
No
Google Cloud Managed Service for Apache Airflow
Yes
Great Expectations
Yes
IRI FieldShield
Yes
Integrations
Amazon Web Services (AWS)
Yes
Ardent
No
Azure SQL Database
Yes
Beats
No
BentoML
No
Cake AI
No
Google Cloud BigQuery
Yes
Google Cloud Managed Service for Apache Airflow
No
Great Expectations
No
IRI FieldShield
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
Consumption-based and annual fixed licensing fee are both available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
Yes
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
Yes
Chromebook
No
Customer Support
Business Hours
No
Live Rep (24/7)
No
Online Support
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
No
Webinars
No
Live Training (Online)
No
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
Yes
Vendor Details
Company Name
The Apache Software Foundation
Founded
1999
Country
United States
Website
airflow.apache.org
Vendor Details
Company Name
FirstEigen
Founded
2015
Country
United States
Website
firsteigen.com/databuck/
Product Features
Workflow Management
Access Controls/Permissions
No
Approval Process Control
No
Business Process Automation
No
Calendar Management
No
Compliance Tracking
No
Configurable Workflow
No
Customizable Dashboard
No
Document Management
No
Forms Management
No
Graphical Workflow Editor
No
Mobile Access
No
No-Code
No
Task Management
No
Third Party Integrations
No
Workflow Configuration
No
Product Features
Big Data
Collaboration
No
Data Blends
No
Data Cleansing
No
Data Mining
No
Data Visualization
No
Data Warehousing
No
High Volume Processing
Yes
No-Code Sandbox
No
Predictive Analytics
No
Templates
No
Data Governance
Access Control
No
Data Discovery
No
Data Mapping
No
Data Profiling
No
Deletion Management
No
Email Management
No
Policy Management
No
Process Management
No
Roles Management
No
Storage Management
No
Data Management
Customer Data
No
Data Analysis
No
Data Capture
No
Data Integration
No
Data Migration
No
Data Quality Control
No
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
No
Data Quality
Address Validation
No
Data Deduplication
No
Data Discovery
No
Data Profililng
Yes
Master Data Management
No
Match & Merge
No
Metadata Management
No
