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Average Ratings 0 Ratings
Description
Daft is an advanced framework designed for ETL, analytics, and machine learning/artificial intelligence at scale, providing an intuitive Python dataframe API that surpasses Spark in both performance and user-friendliness. It integrates seamlessly with your ML/AI infrastructure through efficient zero-copy connections to essential Python libraries like Pytorch and Ray, and it enables the allocation of GPUs for model execution. Operating on a lightweight multithreaded backend, Daft starts by running locally, but when the capabilities of your machine are exceeded, it effortlessly transitions to an out-of-core setup on a distributed cluster. Additionally, Daft supports User-Defined Functions (UDFs) in columns, enabling the execution of intricate expressions and operations on Python objects with the necessary flexibility for advanced ML/AI tasks. Its ability to scale and adapt makes it a versatile choice for data processing and analysis in various environments.
Description
Elevate your security testing experience, from establishing your setup to examining your data processing outcomes, with esDynamic, which streamlines your efforts and saves you precious time while maximizing the effectiveness of your attack strategies. Explore this adaptable and all-encompassing Python-based platform, expertly designed to support every step of your security evaluations. Tailor your research environment to fit your specific needs by seamlessly incorporating new tools, integrating equipment, and adjusting data. Moreover, esDynamic offers a vast repository of resources on intricate subjects that would usually necessitate considerable research or the input of a specialized team, providing immediate access to expert knowledge. Move away from disorganized data and piecemeal information. Embrace a unified workspace that encourages your team to easily exchange data and insights, enhancing collaboration and speeding up the discovery process. Additionally, consolidate and fortify your work within JupyterLab notebooks for streamlined sharing among your team members, ensuring everyone is on the same page. This holistic approach can significantly transform your security testing workflow.
API Access
Has API
API Access
Has API
Integrations
Python
Amazon Web Services (AWS)
Apache Arrow
Apache Iceberg
Apache Spark
Databricks
Delta Lake
Google Cloud Platform
JSON
JupyterLab
Integrations
Python
Amazon Web Services (AWS)
Apache Arrow
Apache Iceberg
Apache Spark
Databricks
Delta Lake
Google Cloud Platform
JSON
JupyterLab
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
Free
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
Daft
Country
United States
Website
www.getdaft.io
Vendor Details
Company Name
eShard
Country
France
Website
eshard.com/esdynamic
Product Features
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports
Product Features
Data Science
Access Control
Advanced Modeling
Audit Logs
Data Discovery
Data Ingestion
Data Preparation
Data Visualization
Model Deployment
Reports
Software Testing
Automated Testing
Black-Box Testing
Dynamic Testing
Issue Tracking
Manual Testing
Quality Assurance Planning
Reporting / Analytics
Static Testing
Test Case Management
Variable Testing Methods
White-Box Testing