Software Alternatives, Accelerators & Startups

neptune.ai VS Uber Engineering

Compare neptune.ai VS Uber Engineering 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.

Uber Engineering logo Uber Engineering

From practice to people
  • 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.

  • Uber Engineering Landing page
    Landing page //
    2023-09-24

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

Uber Engineering

Pricing URL
-
$ Details
-
Platforms
-
Release Date
-

neptune.ai features and specs

  • Experiment Tracking
    Neptune.ai provides comprehensive tools for tracking machine learning experiments, which helps in organizing and managing multiple experiments efficiently.
  • Collaboration Features
    The platform offers collaboration features that allow multiple team members to contribute and monitor the progress of ongoing projects.
  • Integration Capability
    Neptune.ai integrates well with popular machine learning libraries and tools, enabling seamless workflow integration into existing processes.
  • Interactive Dashboard
    It provides a user-friendly interface and interactive dashboard for visualizing and analyzing experiment results, which aids in better decision-making.
  • Model Registry
    Neptune.ai includes a model registry feature that facilitates the management and deployment of machine learning models.

Possible disadvantages of neptune.ai

  • Pricing
    Some users might find the pricing model expensive, especially for small teams or individual users, although they offer a free tier with limited features.
  • Learning Curve
    New users might experience a learning curve when getting started with Neptune.ai due to the rich set of features and capabilities.
  • Limited Offline Access
    The platform primarily functions online, which limits its usability in environments with restricted internet access.
  • Integration Complexity
    While the platform offers numerous integrations, setting them up might be complex and time-consuming for users unfamiliar with such processes.
  • Technical Support
    Some users have reported that the response time for technical support could be improved, especially for immediate assistance needs.

Uber Engineering features and specs

  • Innovative Solutions
    Uber Engineering works on cutting-edge technologies and innovative solutions to complex problems, offering engineers the opportunity to tackle challenging and impactful projects.
  • Scalable Systems
    The team is known for its ability to create scalable and robust systems that handle millions of transactions and users worldwide, providing valuable experience in high-volume system architecture.
  • Diverse Technical Areas
    Uber Engineering covers a wide range of technical domains including distributed systems, data science, AI and machine learning, which allows engineers to broaden their expertise.
  • Open Source Contributions
    Uber Engineering often contributes to the open-source community, which can enhance public visibility and offers engineers the opportunity to contribute to and improve widely-used software.

Possible disadvantages of Uber Engineering

  • High Pressure Environment
    Working in a fast-paced, high-pressure environment can lead to stress and burnout for some engineers, as there is often a strong focus on rapid delivery and continuous improvement.
  • Complex Legacy Systems
    Engineers may need to work with complex legacy systems, which can be difficult to manage and update, potentially hindering innovation and requiring significant maintenance work.
  • Rapid Change
    Frequent changes in technology strategy and product focus can make it challenging to have a long-term impact, requiring engineers to be adaptable and open to shifting priorities.
  • Resource Intensive
    Building and maintaining large-scale systems is resource-intensive in terms of both time and computational power, which can lead to constraints and bottlenecks that need to be managed effectively.

neptune.ai videos

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

Uber Engineering videos

Engineering at Seattle | Uber Engineering | Uber

More videos:

  • Review - Engineering at Amsterdam | Uber Engineering | Uber

Category Popularity

0-100% (relative to neptune.ai and Uber Engineering)
Data Science And Machine Learning
AI
54 54%
46% 46
Data Science Notebooks
100 100%
0% 0
Productivity
0 0%
100% 100

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 Uber Engineering

neptune.ai Reviews

  1. anonymous for now
    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

Uber Engineering Reviews

We have no reviews of Uber Engineering yet.
Be the first one to post

Social recommendations and mentions

Based on our record, neptune.ai seems to be more popular. It has been mentiond 24 times since March 2021. 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 (24)

  • Understanding the MLOps Lifecycle
    Some tools for model validation include Neptune AI, Kolena, and Censius. - Source: dev.to / 10 months ago
  • 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 / over 1 year 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 / over 1 year 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 โ€œcopy-pasteโ€ their approach as a baseline (think Tailscale, DigitalOCean, Vercel, Algolia, CircleCi, Supabase,... - Source: Hacker News / almost 2 years 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: about 2 years ago
View more

Uber Engineering mentions (0)

We have not tracked any mentions of Uber Engineering yet. Tracking of Uber Engineering recommendations started around Dec 2022.

What are some alternatives?

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

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

Intelec AI - Automate building and deploying machine learning models

Weights & Biases - Developer tools for deep learning research

Akkio - No-Code AI models right from your browser

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.

Apple - Available on iOS