Software Alternatives, Accelerators & Startups

Obviously.ai VS Google Open Source

Compare Obviously.ai VS Google Open Source and see what are their differences

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.

Obviously.ai logo Obviously.ai

The entire process of running Data Science - building Machine Learning algorithm, explaining results and predicting outcomes, packed in one single click.

Google Open Source logo Google Open Source

All of Googles open source projects under a single umbrella
  • Obviously.ai Landing page
    Landing page //
    2023-03-24
  • Google Open Source Landing page
    Landing page //
    2023-09-22

Obviously.ai features and specs

  • User-Friendly Interface
    Obviously.ai offers a simple, intuitive interface that allows users with no coding experience to create AI models, making it accessible to a broader audience.
  • Fast Model Creation
    The platform claims to generate AI models in minutes, enabling rapid prototyping and testing without significant time investment.
  • Data Transformation and Preparation
    Provides built-in tools for cleaning and preparing data, which can save users time and reduce the need for third-party data manipulation tools.
  • Integration Features
    Easily integrates with various data sources and services, allowing seamless workflow incorporation into existing business processes.
  • Detailed Insights and Interpretability
    Offers insights and explanations for the models, helping users understand the decisions and functionality of their AI solutions.

Possible disadvantages of Obviously.ai

  • Limited Customization
    While user-friendly, the platform may not offer the depth of customization or flexibility desired by experienced data scientists or developers seeking more control over model parameters.
  • Scalability Concerns
    Potentially less suitable for very large datasets or highly complex models, which might limit use cases for larger enterprises or advanced applications.
  • Dependency on Platform
    Relying on a SaaS platform can lead to issues with data privacy, long-term costs, and dependency on a third-party service for business-critical operations.
  • Feature Limitations
    Some advanced AI and machine learning features might be missing or simplified, which could be a drawback for users requiring edge-case solutions.
  • Pricing
    Potentially high costs associated with premium features and capabilities, particularly if usage scales beyond basic needs.

Google Open Source features and specs

  • Community Support
    Google Open Source projects often have large, active communities that contribute to the software's development and provide support.
  • Innovation
    Google frequently publishes cutting-edge projects, allowing developers to utilize the latest in technology and innovation.
  • Quality Documentation
    Google Open Source projects generally come with comprehensive documentation, making it easier for developers to integrate and utilize their tools.
  • Scalability
    Many of Google's open-source projects are designed to scale efficiently, benefiting from Google's extensive experience in handling large-scale systems.
  • Integration with Other Google Services
    Open-source projects from Google often integrate smoothly with other Google services and platforms, providing a cohesive ecosystem.

Possible disadvantages of Google Open Source

  • Dependency on Google
    Being tied to Google ecosystems might lead to dependencies, making it harder for developers to switch to other alternatives.
  • Data Privacy Concerns
    Some developers are wary of data privacy issues when using tools developed by Google, given the company's history with data collection.
  • Complexity
    Google’s projects can sometimes be complex, requiring a steep learning curve for developers who are not familiar with their systems and methodologies.
  • Licensing Issues
    Open-source licensing can sometimes pose challenges, especially for companies trying to ensure compliance with multiple licensing requirements.
  • Longevity and Support
    Not all Google open-source projects have long-term support, and there is a risk that some projects may be abandoned or shelved.

Analysis of Google Open Source

Overall verdict

  • Google Open Source is generally regarded positively within the developer community due to its significant contributions to widely-used projects and its commitment to maintaining open and collaborative development practices.

Why this product is good

  • Google Open Source (opensource.google) is considered good because it hosts a wide array of high-quality projects that are well-maintained and actively supported by Google and the community. These projects often adhere to strong industry standards, providing reliable tools and libraries that developers around the world can use. Additionally, the open-source nature allows developers to contribute, inspect the source code, and modify it to fit their needs, which promotes transparency and innovation.

Recommended for

    This is recommended for developers looking for mature, scalable, and robust open-source solutions. It’s also ideal for organizations seeking to build upon a reliable foundation of tools, tech enthusiasts eager to learn and contribute to open source projects, and anyone interested in the collaborative world of software development.

Obviously.ai videos

AIxDesign Keynote: No-Code ML with obviously.ai

Google Open Source videos

No Google Open Source videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Obviously.ai and Google Open Source)
Data Science And Machine Learning
Developer Tools
0 0%
100% 100
AI
100 100%
0% 0
Productivity
0 0%
100% 100

User comments

Share your experience with using Obviously.ai and Google Open Source. 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 Obviously.ai and Google Open Source

Obviously.ai Reviews

33+ Best No Code Tools you will love 😍
With Obviously AI, you can run complex ML predictions, analytics and look at outcomes of data in very little time (on their site they even say in just one click). It means that even someone with no data science or even deep analytics experience, can run models with ease and gain valuable insights.

Google Open Source Reviews

We have no reviews of Google Open Source yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Google Open Source seems to be a lot more popular than Obviously.ai. While we know about 25 links to Google Open Source, we've tracked only 2 mentions of Obviously.ai. 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.

Obviously.ai mentions (2)

  • Awesome No-Code Data Wrangling Tools
    I just got access to the beta version this new tool called databite.net. I am a data science student so I do a lot of data wrangling on a daily basis, but this thing basically does all of the cleaning for you. I uploaded some CVSs and it immediately joined the files together, added a date index and interpolated missing values, etc. Just like that. I then gave me some options for plots (simple time series, scatter... Source: over 2 years ago
  • Machine learning anyone?
    What about AutoML tools like C3.ai, higgs.ai, obviously.ai ?Anyone using those for trading? With human in the loop ofc, you're right there. Source: about 3 years ago

Google Open Source mentions (25)

View more

What are some alternatives?

When comparing Obviously.ai and Google Open Source, you can also consider the following products

Akkio - No-Code AI models right from your browser

LaunchKit - Open Source - A popular suite of developer tools, now 100% open source.

Google Cloud Machine Learning - Google Cloud Machine Learning is a service that enables user to easily build machine learning models, that work on any type of data, of any size.

GitHub Sponsors - Get paid to build what you love on GitHub

Predicto - Make predictions on the Blockchain

Open Collective - Recurring funding for groups.