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Average Ratings 0 Ratings

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ease
features
design
support

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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

The RAPIDS software library suite, designed on CUDA-X AI, empowers users to run comprehensive data science and analytics workflows entirely on GPUs. It utilizes NVIDIA® CUDA® primitives for optimizing low-level computations while providing user-friendly Python interfaces that leverage GPU parallelism and high-speed memory access. Additionally, RAPIDS emphasizes essential data preparation processes tailored for analytics and data science, featuring a familiar DataFrame API that seamlessly integrates with various machine learning algorithms to enhance pipeline efficiency without incurring the usual serialization overhead. Moreover, it supports multi-node and multi-GPU setups, enabling significantly faster processing and training on considerably larger datasets. By incorporating RAPIDS, you can enhance your Python data science workflows with minimal code modifications and without the need to learn any new tools. This approach not only streamlines the model iteration process but also facilitates more frequent deployments, ultimately leading to improved machine learning model accuracy. As a result, RAPIDS significantly transforms the landscape of data science, making it more efficient and accessible.

API Access

Has API

API Access

Has API

Screenshots View All

Screenshots View All

Integrations

Apache Spark
Databricks
Amazon Web Services (AWS)
Apache Arrow
Apache Iceberg
Capital One Spark Business Banking
Delta Lake
Domino Enterprise AI Platform
Google Cloud Platform
Iguazio
JSON
Microsoft Azure
NVIDIA FLARE
Plotly Dash
Python
Rust
Unity Catalog
pandas

Integrations

Apache Spark
Databricks
Amazon Web Services (AWS)
Apache Arrow
Apache Iceberg
Capital One Spark Business Banking
Delta Lake
Domino Enterprise AI Platform
Google Cloud Platform
Iguazio
JSON
Microsoft Azure
NVIDIA FLARE
Plotly Dash
Python
Rust
Unity Catalog
pandas

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

Daft

Country

United States

Website

www.getdaft.io

Vendor Details

Company Name

NVIDIA

Founded

1993

Country

United States

Website

developer.nvidia.com/rapids

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

Alternatives

Alternatives