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GitLab VS BigML

Compare GitLab VS BigML and see what are their differences

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GitLab logo GitLab

Create, review and deploy code together with GitLab open source git repo management software | GitLab

BigML logo BigML

BigML's goal is to create a machine learning service extremely easy to use and seamless to integrate.
  • GitLab Landing page
    Landing page //
    2023-10-17
  • BigML Landing page
    Landing page //
    2022-10-08

GitLab

Website
about.gitlab.com
Pricing URL
Official GitLab Pricing
Release Date
2014 January
Startup details
Country
United States
State
California
City
San Francisco
Founder(s)
Dmitriy Zaporozhets
Employees
1,000 - 1,999
Edit details

BigML

Website
bigml.com
Pricing URL
Official BigML Pricing
Release Date
-
Edit details

GitLab features and specs

  • Integrated DevOps Platform
    GitLab provides a single application for the entire DevOps lifecycle, which simplifies the workflow and reduces the need for multiple tools.
  • CI/CD Capabilities
    It offers powerful Continuous Integration and Continuous Deployment (CI/CD) features, enabling automated testing and deployment.
  • Self-Hosted and SaaS Options
    GitLab can be hosted on your own servers or used as a cloud-hosted service, providing flexibility depending on your needs.
  • Strong Security Features
    GitLab includes various security features such as code quality analysis, vulnerability management, and compliance management.
  • Robust Community and Support
    There is a large community and extensive documentation available, along with professional support options.

Possible disadvantages of GitLab

  • Complexity for New Users
    The extensive features and functionalities can be overwhelming for newcomers, requiring a steep learning curve.
  • Resource Intensive
    Self-hosting a GitLab instance requires substantial server resources, which can be costly.
  • Price
    While there is a free tier, the advanced features are part of the paid plans, which can be expensive for small teams or startups.
  • User Interface
    Some users find the interface less intuitive and harder to navigate compared to other platforms like GitHub.
  • Performance Issues
    Large repositories or high usage can sometimes lead to performance issues, especially on self-hosted instances.

BigML features and specs

  • User-Friendly Interface
    BigML offers an intuitive web-based interface that makes it easy for users to build and deploy machine learning models without deep technical knowledge.
  • Wide Range of Algorithms
    It supports various machine learning algorithms, including regression, classification, clustering, and anomaly detection, catering to diverse use cases.
  • Ease of Integration
    BigML provides robust API support, allowing seamless integration with other applications and systems for streamlined workflows.
  • Visualization Tools
    The platform includes powerful visualization tools that help in understanding data, model performance, and results, aiding in better decision-making.
  • Scalability
    BigML's cloud-based infrastructure allows it to scale easily, handling large datasets and complex models efficiently.
  • Automated Workflows
    It offers automation features like WhizzML for creating automated workflows and advanced scripts, making repetitive tasks simpler.

Possible disadvantages of BigML

  • Cost
    The pricing structure can be a limiting factor for startups or individual users, especially when dealing with large amounts of data.
  • Limited Customization
    While the platform offers many pre-built algorithms, there is limited scope for customization compared to building models from scratch using open-source libraries.
  • Learning Curve
    Despite its user-friendly design, there can be a learning curve for those unfamiliar with machine learning concepts, particularly for advanced features.
  • Dependency on Internet
    As a cloud-based service, users need a reliable internet connection to access and utilize BigML's features, which can be a drawback in areas with poor connectivity.
  • Data Privacy Concerns
    Using a cloud-based service can raise data privacy and security concerns, particularly for sensitive or proprietary data.

Analysis of GitLab

Overall verdict

  • Yes, GitLab is generally considered a good platform, especially for teams looking for an integrated set of tools for software development and DevOps. Its features and flexibility make it a strong choice for many organizations.

Why this product is good

  • GitLab is a popular DevOps platform that provides a comprehensive suite of tools for software development, including version control, issue tracking, continuous integration/continuous deployment (CI/CD), and more. It is valued for its open-source model, strong security features, user-friendly interface, and a wide range of integrations. GitLab's all-in-one approach allows teams to manage their entire DevOps lifecycle from a single application, which can help improve collaboration and efficiency.

Recommended for

    GitLab is well-suited for developers, DevOps engineers, project managers, and teams that require robust CI/CD capabilities, strong security features, and an open-source platform that can be self-hosted or used as a cloud service. It is particularly beneficial for organizations looking for a comprehensive solution to streamline their development workflows.

Analysis of BigML

Overall verdict

  • BigML is a good choice for users seeking an accessible and efficient machine learning platform. Its combination of ease of use, flexibility, and robust features allows for effective data analysis and model deployment, making it suitable for many use cases.

Why this product is good

  • BigML is a popular machine learning platform known for its user-friendly interface and comprehensive suite of tools that cater to both beginners and experts. It offers a wide range of machine learning models and allows for seamless integration with other tools and workflows. Users appreciate its ease of use, scalability, and ability to handle various types of data. Additionally, BigML provides extensive documentation and support, making it an attractive option for those looking to implement machine learning solutions without extensive coding knowledge.

Recommended for

  • Data scientists and analysts looking for an intuitive platform to build and deploy models.
  • Businesses aiming to integrate machine learning into their operations without a steep learning curve.
  • Educators and students who wish to explore machine learning concepts hands-on.
  • Developers needing a scalable solution with ample API support for custom applications.
  • Organizations looking for a reliable and secure cloud-based machine learning solution.

GitLab videos

+ Add

Introduction to GitLab Workflow

More videos:

  • Review - GitLab Review App Working Session

BigML videos

+ Add

BigML is Machine Learning for Everyone

More videos:

  • Review - BigML Spring 2016 Webinar - WhizzML!

Category Popularity

0-100% (relative to GitLab and BigML)

GitLab

BigML

Code Collaboration
100 100%
Code Collaboration
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Git
100 100%
Git
0% 0
Data Science Tools
0 0%
Data Science Tools
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 GitLab and BigML

GitLab Reviews

  1. Reinhard
    · Boss at CLOUD Meister ·
    perfect for Freelancers!
The Top 11 Static Application Security Testing (SAST) Tools
GitLab’s in-context testing solution simplifies the development process by automating both application and infrastructure management on a single platform.Why We Picked GitLab: We like GitLab’s automation of testing and compliance across development workflows. Its in-context testing minimizes license costs and reduces the learning curve.
Source: expertinsights.com
The Top 10 GitHub Alternatives
GitLab is a web-based DevSecOps (take that, Call of Duty) platform that allows software development teams to plan, build, and ship secure code all in one application. GitLab offers a range of features and tools to support the entire software development lifecycle, from project planning and source code management to continuous integration, delivery, and deployment.
Source: www.wearedevelopers.com
The Best Alternatives to Jenkins for Developers
CI/CD GitLab, as a complete DevOps platform, provides an integrated CI/CD solution along with its other features. If your team is already using GitLab for controlling versions and managing projects, the addition of GitLab CI/CD can be very smooth. The offering in CI/CD by GitLab is quite customizable and it backs up many programming languages as well as application test...
Source: morninglif.com
Top 7 GitHub Alternatives You Should Know (2024)
Most of the listed alternatives offer free tier plans for individuals or small teams. Tools like GitLab and Bitbucket allow users to host unlimited repositories without cost.
Source: snappify.com
Best GitHub Alternatives for Developers in 2023
While GitLab features an extensive set of capabilities, this can also serve as a weakness since beginners may find the developer tool overwhelming to begin with. The user interface compounds this issue by being outdated and unintuitive. GitLab could benefit from more third-party integrations, and its performance tends to struggle when dealing with large repositories or CI/CD...
Source: www.techrepublic.com

BigML Reviews

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

Social recommendations and mentions

Based on our record, GitLab seems to be a lot more popular than BigML. While we know about 134 links to GitLab, we've tracked only 2 mentions of BigML. 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.

GitLab mentions (134)

  • GitLab: templates for Merge Requests
    GitLab is a well-established tool that hardly needs any introduction. This article is more like some notes to my future self. - Source: dev.to / 1 day ago
  • India Open Source Development: Harnessing Collaborative Innovation for Global Impact
    Indian developers have embraced platforms like GitHub and GitLab, which serve as global meeting points for coding projects. Developer communities such as FOSSAsia and Open Source India regularly organize hackathons, webinars, and code sprints that bring together enthusiasts to tackle both local and global problems. - Source: dev.to / 25 days ago
  • Open Source Funding: Strategies, Case Studies, and Best Practices
    In this article, we explore funding methods that empower projects such as Red Hat, GitLab, and Blender. Our discussion focuses on overlaying robust financial models with community-led efforts while incorporating advanced technologies like blockchain and smart contracts for secure, transparent fund distribution. With clear definitions, tables, bullet lists, and real-world examples, we aim to provide a holistic view... - Source: dev.to / about 2 months ago
  • The Hidden Challenges of Building with AWS
    💡** My Take:** If you’re not ready to spend hours debugging AWS configurations, you might want to consider other cloud options, such as DigitalOcean or Gitlab for CI/CD. - Source: dev.to / 2 months ago
  • Understanding Open Source Developer Support Networks
    The foundation of OSS is its community. OSDSNs offer platforms like GitHub and GitLab that encourage communication and collaboration, creating a sense of belonging among developers. These platforms are essential for managing projects and enhancing motivation within the community. - Source: dev.to / 3 months ago
View more

BigML mentions (2)

  • Free for dev - list of software (SaaS, PaaS, IaaS, etc.)
    Bigml.com — Hosted machine learning algorithms. Unlimited free tasks for development, limit of 16 MB data/task. - Source: dev.to / almost 4 years ago
  • Theory: The price action was intentionally manipulated to prevent any AI from being able to predict it. First time this model shows as flat. Forever.
    They know the website is bigml.com it's possible they have many magnitudes better algorithms to predict this shit. And it's also possible they paid some quants to come up with price action that just completely fucks with BigML's algorithm entirely to make it look flat. Source: about 4 years ago

What are some alternatives?

When comparing GitLab and BigML, you can also consider the following products

GitHub - Originally founded as a project to simplify sharing code, GitHub has grown into an application used by over a million people to store over two million code repositories, making GitHub the largest code host in the world.

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

BitBucket - Bitbucket is a free code hosting site for Mercurial and Git. Manage your development with a hosted wiki, issue tracker and source code.

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Gitea - A painless self-hosted Git service

Qubole - Qubole delivers a self-service platform for big aata analytics built on Amazon, Microsoft and Google Clouds.

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