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Dask vs Jovian: What are the differences?
What is Dask? A flexible library for parallel computing in Python. It is a versatile tool that supports a variety of workloads. It is composed of two parts: Dynamic task scheduling optimized for computation. This is similar to Airflow, Luigi, Celery, or Make, but optimized for interactive computational workloads Big Data collections like parallel arrays, dataframes, and lists that extend common interfaces like NumPy, Pandas, or Python iterators to larger-than-memory or distributed environments. These parallel collections run on top of dynamic task schedulers. .
What is Jovian? Tooling and workflows built specifically for data science. It is a better place for your data science projects, Jupyter notebooks, machine learning models, experiment logs, results, and more.
Dask and Jovian can be categorized as "Data Science" tools.
Some of the features offered by Dask are:
- Supports a variety of workloads
- Dynamic task scheduling
- Trivial to set up and run on a laptop in a single process
On the other hand, Jovian provides the following key features:
- Collaboration platform built for data science
- Simple Jupyter notebook versioning
- Compare and analyze experiments
