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Description
Azkaban serves as a distributed Workflow Manager developed by LinkedIn to address the complexities of Hadoop job dependencies. There were instances where jobs required a specific order of execution, ranging from ETL processes to data analysis applications. Following the release of version 3.0, Azkaban offers two distinct operational modes: the standalone “solo-server” mode and the distributed multiple-executor mode. The solo-server mode utilizes an embedded H2 database, allowing both the web server and executor server to operate within the same process, making it ideal for initial experimentation or small-scale applications. In contrast, the multiple-executor mode is designed for serious production environments, requiring a MySQL database configured with a master-slave arrangement. Ideally, the web server and executor servers are hosted on separate machines to ensure that system upgrades and maintenance do not disrupt user experience. This configuration not only enhances Azkaban’s robustness but also significantly improves its scalability, making it suitable for larger, more complex workflows. By offering these two modes, Azkaban caters to a wide range of user needs, from casual experimentation to enterprise-level deployments.
Description
Organizations are increasingly focused on becoming more data-driven, implementing dashboards, analytics, and data pipelines throughout the contemporary data landscape. However, many organizations face significant challenges with data reliability, which can lead to misguided business decisions and a general mistrust in data that negatively affects their financial performance. Addressing intricate data challenges is often a labor-intensive process that requires collaboration among various teams, all of whom depend on informal knowledge to painstakingly reverse engineer complex data pipelines spanning multiple platforms in order to pinpoint root causes and assess their implications. Pantomath offers a solution as a data pipeline observability and traceability platform designed to streamline data operations. By continuously monitoring datasets and jobs within the enterprise data ecosystem, it provides essential context for complex data pipelines by generating automated cross-platform technical pipeline lineage. This automation not only enhances efficiency but also fosters greater confidence in data-driven decision-making across the organization.
API Access
Has API
API Access
Has API
Integrations
Amazon Redshift
Amazon S3
Auth0
Azure Data Factory
Azure Data Lake Storage
Azure Synapse Analytics
BMC Helix Control-M
Google Chat
Hadoop
IBM DataStage
Integrations
Amazon Redshift
Amazon S3
Auth0
Azure Data Factory
Azure Data Lake Storage
Azure Synapse Analytics
BMC Helix Control-M
Google Chat
Hadoop
IBM DataStage
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Azkaban
Website
azkaban.github.io
Vendor Details
Company Name
Pantomath
Founded
2022
Country
United States
Website
www.getpantomath.com