Software Alternatives, Accelerators & Startups

neptune.ai VS datarobot

Compare neptune.ai VS datarobot and see what are their differences

neptune.ai logo neptune.ai

Neptune brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed and shared with others. Works with all common technologies and integrates with other tools.

datarobot logo datarobot

Become an AI-Driven Enterprise with Automated Machine Learning
  • neptune.ai Landing page
    Landing page //
    2023-08-24

Track and version your notebooks Log all your notebooks directly from Jupyter or Jupyter Lab. All you need is to install a Jupyter extension.

Manage your experimentation process Neptune tracks your work with virtually no interference to the way you like to do it. Decide what is relevant to your project and start tracking: - Metrics - Hyperparameters - Data versions - Model files - Images - Source code

Integrate with your workflow easily Neptune is a lightweight extension to your current workflow. Works with all common technologies in data science domain and integrates with other tools. It will take you 5 minutes to get started.

  • datarobot Landing page
    Landing page //
    2023-08-01

neptune.ai

Website
neptune.ai
$ Details
freemium
Platforms
Python
Release Date
2018 April
Startup details
Country
Poland
State
Mazowieckie
City
Warsaw
Founder(s)
Piotr Niedzwiedz
Employees
10 - 19

datarobot

Pricing URL
-
$ Details
Platforms
-
Release Date
2012 January
Startup details
Country
United States
City
Boston
Founder(s)
Jeremy Achin
Employees
1,000 - 1,999

neptune.ai videos

Machine Learning Experiment Management with Neptune.ai - How to start

datarobot videos

Build and Deploy a Managed Machine Learning Project in 10 minutes - Scott Lutz (DataRobot)

More videos:

  • Review - How DataRobot Works
  • Review - DataRobot Predictions Using Alteryx

Category Popularity

0-100% (relative to neptune.ai and datarobot)
Data Science And Machine Learning
Data Science Notebooks
100 100%
0% 0
Business & Commerce
0 0%
100% 100
Machine Learning
100 100%
0% 0

User comments

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Reviews

These are some of the external sources and on-site user reviews we've used to compare neptune.ai and datarobot

neptune.ai Reviews

  1. Easy to use, not overdone, good for model management and collab

    Only negative is I didn't see it integrated with Azure, does with Google, AWS and one more. Looks real nice, and pretty powerful and plenty useful features for a data science group

datarobot Reviews

The 16 Best Data Science and Machine Learning Platforms for 2021
Description: DataRobot offers an enterprise AI platform that automates the end-to-end process for building, deploying, and maintaining AI. The product is powered by open-source algorithms and can be leveraged on-prem, in the cloud or as a fully-managed AI service. DataRobot includes several independent but fully integrated tools (Paxata Data Preparation, Automated Machine...

Social recommendations and mentions

Based on our record, neptune.ai seems to be a lot more popular than datarobot. While we know about 23 links to neptune.ai, we've tracked only 1 mention of datarobot. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

neptune.ai mentions (23)

  • A step-by-step guide to building an MLOps pipeline
    Experiment tracking tools like MLflow, Weights and Biases, and Neptune.ai provide a pipeline that automatically tracks meta-data and artifacts generated from each experiment you run. Although they have varying features and functionalities, experiment tracking tools provide a systematic structure that handles the iterative model development approach. - Source: dev.to / 14 days ago
  • A list of SaaS, PaaS and IaaS offerings that have free tiers of interest to devops and infradev
    Neptune.ai - Log, store, display, organize, compare, and query all your MLOps metadata. Free for individuals: 1 member, 100 GB of metadata storage, 200h of monitoring/month. - Source: dev.to / 4 months ago
  • Show HN: A gallery of dev tool marketing examples
    Hi I am Jakub. I run marketing at a dev tool startup https://neptune.ai/ and I share learnings on dev tool marketing on my blog https://www.developermarkepear.com/. Whenever I'd start a new marketing project I found myself going over a list of 20+ companies I knew could have done something well to “copy-paste” their approach as a baseline (think Tailscale, DigitalOCean, Vercel, Algolia, CircleCi, Supabase,... - Source: Hacker News / 9 months ago
  • How to structure/manage a machine learning experiment? (medical imaging)
    There are a lot of tools out there for experiment tracking (eg neptune.ai), but I'm really not sure whether that sort of thing is over the top for what I need to do. Source: 10 months ago
  • How to grow a developer blog to 3M annual visitors? with Jakub Czakon (Neptune.ai)
    Welcome to another episode of The Developer-led Podcast, where we dive into the strategies modern companies use to build and grow their developer tools. In this exciting episode, we're joined by Jakub Czakon, the CMO at Neptune.ai, a startup that assists developers in efficiently managing their machine-learning model data. Jakub is renowned not only for his role at Neptune.ai but also for his developer marketing... - Source: dev.to / 10 months ago
View more

datarobot mentions (1)

  • Predicting the End of Season Bundesliga Table
    To predict what we would have expected, we used the models and approach we developed to predict the knockout stage of the Champions League using data provided by Data Sports Group.  We used DataRobot’s models to predict which team would win each match to simulate the final nine matchdays 10,000 times.  For each team, we calculated the average number of wins, draws and losses over those 10,000 seasons to build an... Source: about 1 year ago

What are some alternatives?

When comparing neptune.ai and datarobot, you can also consider the following products

Algorithmia - Algorithmia makes applications smarter, by building a community around algorithm development, where state of the art algorithms are always live and accessible to anyone.

RapidMiner - RapidMiner is a software platform for data science teams that unites data prep, machine learning, and predictive model deployment.

Comet.ml - Comet lets you track code, experiments, and results on ML projects. It’s fast, simple, and free for open source projects.

Dataiku - Dataiku is the developer of DSS, the integrated development platform for data professionals to turn raw data into predictions.

Weights & Biases - Developer tools for deep learning research

Alteryx - Alteryx provides an indispensable and easy-to-use analytics platform for enterprise companies making critical decisions that drive their business strategy and growth.