Audience

Enterprises requiring a solution that provides advanced parallelism for analytics, enabling performance at scale

About Dask

Dask is open source and freely available. It is developed in coordination with other community projects like NumPy, pandas, and scikit-learn. Dask uses existing Python APIs and data structures to make it easy to switch between NumPy, pandas, scikit-learn to their Dask-powered equivalents. Dask's schedulers scale to thousand-node clusters and its algorithms have been tested on some of the largest supercomputers in the world. But you don't need a massive cluster to get started. Dask ships with schedulers designed for use on personal machines. Many people use Dask today to scale computations on their laptop, using multiple cores for computation and their disk for excess storage. Dask exposes lower-level APIs letting you build custom systems for in-house applications. This helps open source leaders parallelize their own packages and helps business leaders scale custom business logic.

Integrations

API:
Yes, Dask offers API access

Ratings/Reviews

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Company Information

Dask
Founded: 2019
dask.org

Videos and Screen Captures

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Product Details

Platforms Supported
Cloud
Training
Documentation
Videos
Support
Online

Dask Frequently Asked Questions

Q: What kinds of users and organization types does Dask work with?
Q: What languages does Dask support in their product?
Q: What other applications or services does Dask integrate with?
Q: Does Dask have an API?
Q: What type of training does Dask provide?

Dask Product Features

Data Science

Data Ingestion
Data Preparation
Data Visualization
Data Discovery
Advanced Modeling
Model Deployment
Access Control
Audit Logs
Reports