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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
Tarsal's capability for infinite scalability ensures that as your organization expands, it seamlessly adapts to your needs. With Tarsal, you can effortlessly change the destination of your data; what serves as SIEM data today can transform into data lake information tomorrow, all accomplished with a single click. You can maintain your SIEM while gradually shifting analytics to a data lake without the need for any extensive overhaul. Some analytics may not be compatible with your current SIEM, but Tarsal empowers you to have data ready for queries in a data lake environment. Since your SIEM represents a significant portion of your expenses, utilizing Tarsal to transfer some of that data to your data lake can be a cost-effective strategy. Tarsal stands out as the first highly scalable ETL data pipeline specifically designed for security teams, allowing you to easily exfiltrate vast amounts of data in just a few clicks. With its instant normalization feature, Tarsal enables you to route data efficiently to any destination of your choice, making data management simpler and more effective than ever. This flexibility allows organizations to maximize their resources while enhancing their data handling capabilities.
API Access
Has API
API Access
Has API
Integrations
AWS CloudTrail
Amazon S3
Auth0
Box
Cisco Duo
Coda
Databricks
Facebook
GitHub
Hadoop
Integrations
AWS CloudTrail
Amazon S3
Auth0
Box
Cisco Duo
Coda
Databricks
Facebook
GitHub
Hadoop
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
Tarsal
Country
United States
Website
tarsal.co
Product Features
Product Features
Data Security
Alerts / Notifications
Antivirus/Malware Detection
At-Risk Analysis
Audits
Data Center Security
Data Classification
Data Discovery
Data Loss Prevention
Data Masking
Data-Centric Security
Database Security
Encryption
Identity / Access Management
Logging / Reporting
Mobile Data Security
Monitor Abnormalities
Policy Management
Secure Data Transport
Sensitive Data Compliance