Software Alternatives, Accelerators & Startups
Register | Login

OpenStack VS neptune.ai

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

Electe
Illuminate the future with AI featured
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.
Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

OpenStack logo OpenStack

OpenStack software controls large pools of compute, storage, and networking resources throughout a datacenter, managed through a dashboard or via the OpenStack API.

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.
  • OpenStack Landing page
    Landing page //
    2023-07-22
  • 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.

OpenStack

Website
openstack.org
Pricing URL
-
$ Details
Platforms
-
Release Date
-
Edit details

neptune.ai

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

OpenStack features and specs

  • Open Source
    OpenStack is open source, which means there is no licensing fee and a broad community of users and developers contributes to its development and support.
  • Flexibility
    It supports a wide variety of hardware and software, allowing organizations to customize their cloud infrastructure to meet specific needs.
  • Scalability
    OpenStack can scale horizontally, allowing organizations to add or remove resources as their needs change, effectively managing large pools of compute, storage, and networking resources.
  • Vendor Neutrality
    Being vendor-neutral, OpenStack offers flexibility to avoid vendor lock-in and choose from a wide range of compatible technologies and service providers.
  • Community Support
    A large and active community provides extensive documentation, forums, and support, which can be very helpful for troubleshooting and development.

Possible disadvantages of OpenStack

  • Complexity
    Setting up and managing OpenStack can be complex and requires a significant level of expertise, which may necessitate specialized training for staff.
  • Performance Overhead
    Being a feature-rich platform, it often involves more performance overhead compared to other simpler, more streamlined services.
  • Resource Intensive
    OpenStack can be resource-intensive in terms of CPU, memory, and storage, which might not be suitable for all organizations, especially smaller ones with limited resources.
  • Interoperability Issues
    Integrating OpenStack with existing systems and third-party tools can sometimes present challenges, especially when dealing with legacy infrastructure.
  • Evolving Platform
    The platform is constantly evolving, which can be both a pro and a con. Keeping up to date with the latest releases and changes can be time-consuming and may require ongoing maintenance.

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.

Analysis of OpenStack

Overall verdict

  • OpenStack can be an excellent choice for businesses and enterprises looking to deploy a cloud infrastructure, particularly if they value flexibility, scalability, and control over their environment. Being open-source, it also offers cost advantages compared to proprietary solutions, provided the organization has the necessary expertise to manage and maintain it. However, it may be challenging for smaller teams without dedicated IT resources due to its complexity and the steep learning curve associated with its deployment and management.

Why this product is good

  • OpenStack is a popular open-source cloud computing platform that enables users to build and manage both public and private clouds. It offers a flexible and scalable solution for organizations that need to handle large amounts of data and infrastructure. OpenStack is developed by a vast community of developers and organizations, ensuring continuous improvement and adaptation to new technologies. It supports a wide range of APIs, which allows for customization and integration with other services and tools.

Recommended for

    OpenStack is particularly recommended for large enterprises, organizations with skilled IT teams, academic institutions, and service providers that need a highly customizable and scalable cloud solution. It's also a great fit for entities with specific compliance requirements or those that need to run a private cloud with tailored configurations.

OpenStack videos

+ Add

OpenStack Summit Primer, The Who, What, Why and How of OpenStack

More videos:

  • Review - Red Hat OpenStack Platform GPU use case
  • Review - Performance Analysis Review for Production OpenStack Private Cloud in SaaS

neptune.ai videos

+ Add

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

Category Popularity

0-100% (relative to OpenStack and neptune.ai)

OpenStack

neptune.ai

Cloud Computing
100 100%
Cloud Computing
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
VPS
100 100%
VPS
0% 0
Data Science Notebooks
0 0%
Data Science Notebooks
100% 100

User comments

Share your experience with using OpenStack and neptune.ai. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

OpenStack Reviews

35+ Of The Best CI/CD Tools: Organized By Category
OpenStack is a cloud framework. It provides users and enterprises with horizontal scale infrastructure. Its tools allow you to compute, store and share data and resources. It also provides self-service administration that users can interact with directly.
Source: www.cloudzero.com

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

Social recommendations and mentions

Based on our record, neptune.ai seems to be a lot more popular than OpenStack. While we know about 24 links to neptune.ai, we've tracked only 2 mentions of OpenStack. 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.

OpenStack mentions (2)

  • Learn OpenStack by Example: Part 1 - Install DevStack
    In my first post, I looked into what is OpenStack and how, if done right, can be quite a powerful ally in our cloud deployment strategies. In this post, I want to start looking at how we can create an application to learn the basics and components of the system. - Source: dev.to / about 5 years ago
  • Learn OpenStack by examples: Part 0 - Summary and Goals
    While searching for solutions and documentation on the various problems I've come across, I would often see references to OpenStack and it got my curiosity going. What is OpenStack? What services does it offer and who owns it? How do I learn to use it? What are it's costs and limitations? - Source: dev.to / about 5 years ago

neptune.ai mentions (24)

  • Understanding the MLOps Lifecycle
    Some tools for model validation include Neptune AI, Kolena, and Censius. - Source: dev.to / over 1 year 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 / about 2 years 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 2 years 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 3 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: almost 3 years ago
View more

What are some alternatives?

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

Linode - We make it simple to develop, deploy, and scale cloud infrastructure at the best price-to-performance ratio in the market.

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.

DigitalOcean - Simplifying cloud hosting. Deploy an SSD cloud server in 55 seconds.

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

Microsoft Azure - Windows Azure and SQL Azure enable you to build, host and scale applications in Microsoft datacenters.

Spell - Deep Learning and AI accessible to everyone

Loading...