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About

Daft is a framework for ETL, analytics and ML/AI at scale. Its familiar Python dataframe API is built to outperform Spark in performance and ease of use. Daft plugs directly into your ML/AI stack through efficient zero-copy integrations with essential Python libraries such as Pytorch and Ray. It also allows requesting GPUs as a resource for running models. Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster. Daft can handle User-Defined Functions (UDFs) in columns, allowing you to apply complex expressions and operations to Python objects with the full flexibility required for ML/AI. Daft runs locally with a lightweight multithreaded backend. When your local machine is no longer sufficient, it scales seamlessly to run out-of-core on a distributed cluster.

About

Google Colab is a free, hosted Jupyter Notebook service that provides cloud-based environments for machine learning, data science, and educational purposes. It offers no-setup, easy access to computational resources such as GPUs and TPUs, making it ideal for users working with data-intensive projects. Colab allows users to run Python code in an interactive, notebook-style environment, share and collaborate on projects, and access extensive pre-built resources for efficient experimentation and learning. Colab also now offers a Data Science Agent automating analysis, from understanding the data to delivering insights in a working Colab notebook (Sequences shortened. Results for illustrative purposes. Data Science Agent may make mistakes.)

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Developers and enterprises in search of a solution to manage their multimodal data

Audience

Data scientists and AI researchers

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

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Reviews/Ratings

Overall 2.5 / 5
ease 3.6 / 5
features 3.1 / 5
design 4.0 / 5
support 2.6 / 5

Pros & Cons from Real Users

Pros

  • Cannot think of any positive apart from that one can login to the account. No positives as such! Pathetic product.
  • It is free or cheap and good for beginners. It offers a platform to start AI for those who don't have appropriate hardware in personal use.
  • Google Colab is absolutely great. It is so good, that some teachers of my otherwise Google-sceptical computer science department used to recommend it for projects in class as it basically does not need any initial setup and is completely free (the "basic" plan). One of the absolute highlights is the RISE-extension, which enables you to run snippets of code when in presentation mode, without having to switch windows. This really is a great way to present code.
  • Used to live up to their motto: one account to rule them all something something. Now it's 15 accounts to make things work.
  • It's online, it could be useful do do machine learning with high GPU computer. It's linked to Google Drive.

Cons

  • Taking the Google Colab pro subscription, the A100 GPU was almost never available. The T4 GPU used to disconnect in only 1-1.5 Hours making a joke of the GPU subscription.
  • It have been two days that I don't get any GPUs even though I paid for Pro. When I was a regular member I used to get those pretty consistently, maybe not fast and fancy, but at least I had something. Now I have nothing! I will not pay a penny any more and I don't case about quotas etc. You offer a deal, you hold to your promise. There was nothing about quotas in the offer that I went for!
  • You can't really make a virtual environment persist longer than for one session. Running the respective cell with all packages to be installed would take a few minutes at most though. The portability and ease of use of this web-based IDE makes up for this disadvantage. Another disadvantage is the limitation of RAM and computing power but this is hardly reached if you are "just" learning and doing prototyping. If you would want for example to train a somewhat bigger model, it could become very unhandy, as you'd have to do a lot of checkpoints (because you keep getting interrupted by Google every few hours) and memory reallocation, but I guess it would not be impossible. Another disadvantage is that resources are not guaranteed. Depending on the general load and on how much ressources you already used in the past, you can not be sure that you get computing power for your code for a longer time. Nevertheless, being able to use it in its basic version for no money is extraordinary and a huge step towards democratization of, for example AI.
  • Removed the ability to mount different drives to one Colab account thereby breaking entire university projects overnight with no warning. Beyond dumb.
  • - extremely slow - lot of crashes - not intuitive at all - poorly documented - bash and shell extremely horrible - no support for python 2.7

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Daft
United States
www.getdaft.io

Company Information

Google
Founded: 1998
United States
colab.research.google.com

Alternatives

Alternatives

Categories

Categories

Integrations

Amazon Web Services (AWS)
Apache Arrow
Apache Spark
BLACKBOX AI
CodeSquire
DagsHub
Databricks
DeOldify
Devin Desktop
Google Workspace
JSON
Jupyter Notebook
Model Context Protocol (MCP)
MusicGen
Open Interpreter
PyTorch
Python
Visual Studio Code
neptune.ai
pandas

Integrations

Amazon Web Services (AWS)
Apache Arrow
Apache Spark
BLACKBOX AI
CodeSquire
DagsHub
Databricks
DeOldify
Devin Desktop
Google Workspace
JSON
Jupyter Notebook
Model Context Protocol (MCP)
MusicGen
Open Interpreter
PyTorch
Python
Visual Studio Code
neptune.ai
pandas
Claim Daft and update features and information
Claim Daft and update features and information
Claim Google Colab and update features and information
Claim Google Colab and update features and information