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Supervisely VS Parse-Server

Compare Supervisely VS Parse-Server and see what are their differences

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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

Supervisely logo Supervisely

Supervisely helps people with and without machine learning expertise to create state-of-the-art...

Parse-Server logo Parse-Server

parse-server. Parse-compatible API server module for Node/Express. JS, 14271, 3819. parse-server-conformance-tests. Conformance tests for parse-server adapters.
  • Supervisely Landing page
    Landing page //
    2023-08-06
  • Parse-Server Landing page
    Landing page //
    2023-09-14

Supervisely features and specs

  • Comprehensive Toolset
    Supervisely offers a wide range of tools for image annotation, data management, and deep learning model training, providing a one-stop solution for computer vision projects.
  • Collaborative Platform
    It supports team collaboration with features for sharing projects, annotating data, and reviewing work, making it easier for teams to work together.
  • High Customizability
    Supervisely allows users to create custom plugins and automation scripts, offering flexibility to tailor the platform according to specific project needs.
  • Extensive Dataset Support
    The platform supports a wide variety of data formats and types, including images, videos, and 3D data, making it versatile for different applications.
  • Integrated Machine Learning
    Supervisely integrates machine learning capabilities, enabling users to train models directly on the platform and test them using their own annotated data.

Possible disadvantages of Supervisely

  • Cost
    Supervisely can be expensive, particularly for small teams or individual users, as it primarily targets enterprise customers.
  • Complexity
    Due to the breadth of features and tools, there may be a steep learning curve for new users, making it more challenging to get started quickly without adequate training.
  • Performance Issues
    Some users may experience performance issues, particularly when handling very large datasets or running multiple simultaneous tasks.
  • Cloud Dependency
    While a cloud-based platform offers accessibility advantages, it also means that users are dependent on internet connectivity and may face latency or downtime problems.
  • Limited Offline Features
    Supervisely's offline functionality is limited, which can be a drawback for users who need to work in environments with restricted or unreliable internet access.

Parse-Server features and specs

  • Open Source
    Parse-Server is open-source, which means it's free to use and you can modify the source code to fit your specific needs. It also benefits from community contributions and improvements.
  • Backend as a Service
    It provides a backend as a service (BaaS), offering out-of-the-box features like data storage, user authentication, and push notifications, which allows developers to focus more on the frontend.
  • Cloud Independence
    You can deploy Parse-Server on any cloud service of your choice, giving you flexibility and control over your server environment, unlike other closed BaaS options.
  • Rich Feature Set
    Parse-Server includes a rich set of features such as live queries, GraphQL support, and file storage, which helps in developing complex applications efficiently.
  • Community Support
    An active community supports Parse-Server, providing regular updates, plugins, and extensions that can help solve common issues and expand the server's capabilities.

Possible disadvantages of Parse-Server

  • Self-Hosting Requirements
    Unlike fully managed BaaS platforms, you need to set up and maintain your own server infrastructure to use Parse-Server, which can be time-consuming and require technical expertise.
  • Limited Native SDKs
    Although Parse-Server provides SDKs for various platforms, it may not offer the same level of support or regular updates as commercial platforms, leading to potential compatibility issues with newer technologies.
  • Scaling Challenges
    Managing and scaling a self-hosted service can be challenging, especially for applications with growing and fluctuating user bases, requiring additional resources and infrastructure management.
  • Potential Feature Lag
    As an open-source project, Parse-Server might lag behind the latest innovations or features that commercial BaaS providers can rapidly implement due to their resources and funding.
  • Community Reliance
    Since Parse-Server is community-driven, critical bug fixes and improvements depend on community input, which can result in slower resolution times compared to proprietary solutions with dedicated support teams.

Analysis of Supervisely

Overall verdict

  • Overall, Supervisely is a good platform for computer vision projects due to its versatility and ease of use. It offers a complete ecosystem that caters to various stages of the machine learning pipeline, making it an efficient choice for both beginners and experienced practitioners.

Why this product is good

  • Supervisely is considered a robust platform for its comprehensive suite of tools designed for computer vision tasks. It provides capabilities for data labeling, neural network training, and deployment. Its user-friendly interface, collaborative features, and support for a wide range of formats and integrations make it appealing to both individual developers and enterprise teams.

Recommended for

  • Data scientists looking for a comprehensive tool for computer vision.
  • Companies needing a collaborative environment for AI projects.
  • Researchers who require a platform with extensive format support and integrations.
  • Developers wanting an easy-to-use interface for data annotation and model training.

Analysis of Parse-Server

Overall verdict

  • Parse-Server is considered a good choice, particularly for developers looking for a flexible, open-source backend solution that avoids vendor lock-in. It offers a robust set of features out of the box, which can significantly accelerate the development process.

Why this product is good

  • Parse-Server is an open-source backend platform that allows developers to build applications faster by leveraging features like user authentication, push notifications, cloud functions, and real-time database capabilities. It is highly customizable, scalable, and can be deployed on any infrastructure. Moreover, it's backed by a strong community and extensive documentation, making troubleshooting and development easier.

Recommended for

    Parse-Server is recommended for startups, small to medium enterprises, and individual developers seeking a cost-effective backend solution with full control over their infrastructure. It's also ideal for projects that require rapid prototyping and deployment, app developers who need pre-built SDKs, and teams looking to migrate away from Parse's legacy hosted services.

Supervisely videos

+ Add

๐Ÿ› ๏ธBasic annotation overview - Supervisely

More videos:

  • Review - Cars annotation in Supervisely: Polygons vs. AI powered tool
  • Tutorial - Yolo v3 Tutorial #2 - Object Detection Training Part 1 - Create a Supervisely Cluster

Parse-Server videos

No Parse-Server videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Supervisely and Parse-Server)

Supervisely

Parse-Server

Image Annotation
100 100%
Image Annotation
0% 0
Developer Tools
0 0%
Developer Tools
100% 100
Data Labeling
100 100%
Data Labeling
0% 0
Design Prototyping
0 0%
Design Prototyping
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 Supervisely and Parse-Server

Supervisely Reviews

We have no reviews of Supervisely yet.
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Parse-Server Reviews

Firebase Alternative: 3 Open-Source ways toย follow
Parse Server comes with a gazillion out-of-the-box features that allows you to get your MVP out quick and effortlessly. Currently, Parse server is the most popular and robust BaaS framework available that helps developers build mobile apps faster without any technical locks. It is an open source version of the Parse backend that can be easily downloaded for free on GitHub....
Source: medium.com

Social recommendations and mentions

Parse-Server might be a bit more popular than Supervisely. We know about 6 links to it since March 2021 and only 6 links to Supervisely. 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.

Supervisely mentions (6)

  • Way to label yolov7 images fast
    Another annotation tool that integrates prediction and training within the application is supervisely supervisely.com., unfortunately it's pretty expensive unless you are satisfied with the community version. I saw that they have an integration for owl-vit, which might be helpful for annotation of animals. https://ecosystem.supervisely.com/apps/serve-owl-vit. Source: about 3 years ago
  • 65 Blog Posts to Learn Data Science
    Hello world. This tutorial is a gentle introduction to building modern text recognition system using deep learning in 15 minutes. It will teach you the main ideas of how to use Keras and Supervisely for this problem. This guide is for anyone who is interested in using Deep Learning for text recognition in images but has no idea where to start. - Source: dev.to / over 3 years ago
  • Bounding Box for Text Annotation
    If they were videos, I would have suggested trying supervise.ly as it has a very good tracking functionality. Source: almost 4 years ago
  • CVAT alternatives for video frame annotation
    Hi, I'm exactly in the same boat like you are. I looked around for a while and the better solutions I found was supervise.ly and CVAT for video annotation. The pricetag on supervisely is pretty high, so I analyzed CVAT for a couple days and was positively surprised. Source: about 4 years ago
  • Accessing 2022 Machine Learning Imagery from WPI's Photo Album
    Under the WPI Photo Ambum section of the page for FRC field photos (https://www.firstinspires.org/robotics/frc/playing-field#WPIPhotos), they have a section of machine learning imagery. However, this link goes to supervise.ly, the website they use for machine learning. I created an account to attempt to download the images, however, whenever I try to 'clone' the project, it stalls at 0% and gives me an error... Source: about 4 years ago
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Parse-Server mentions (6)

  • AI Coding: Building a 1-Hour App Clone Is Easy. Shipping It Is the Work
    If youโ€™re coming from the Parse ecosystem, it may help to know that Parse itself is a long-running open source backend framework. You can start from the official Parse Platform site, or go deeper with the communityโ€™s Parse Server repository. Our own developer docs are organized around that reality. If you want implementation-level guides, start with our SashiDo Documentation. - Source: dev.to / 5 months ago
  • What to choose for backend
    If you like headless CMS / Backend As A Service you should consider https://directus.io/ or https://github.com/parse-community/parse-server. Both nodejs and open source. Source: about 4 years ago
  • Any general purpose visualisation "just add the data" framework
    There's numerous standard backends which frontenders could use in simplistic cases to start, say https://github.com/PostgREST/postgrest or https://github.com/parse-community/parse-server. Source: over 4 years ago
  • Show HN: Caffeine, minimum viable back end for prototyping
    Parse is still around and supported: https://github.com/parse-community/parse-server. - Source: Hacker News / over 4 years ago
  • Ask HN: What Back End Framework with User Management Is Your Favorite?
    I am curious what backend framework you would choose to run with for prototyping an application with run of the mill user management requirements. That is functionality along the lines of: session management, password policies, password reset, user verifications, etc. Sadly it seems there really aren't any frameworks that have user management natively supported. The only one I am aware of is [Parse... - Source: Hacker News / about 5 years ago
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What are some alternatives?

When comparing Supervisely and Parse-Server, you can also consider the following products

Labelbox - Build computer vision products for the real world

Firebase - Firebase is a cloud service designed to power real-time, collaborative applications for mobile and web.

Universal Data Tool - Machine learning, data labeling tool, computer vision, annotate-images, classification, dataset

Marvel - Turn sketches, mockups and designs into web, iPhone, iOS, Android and Apple Watch app prototypes.

CrowdFlower - Enterprise crowdsourcing for micro-tasks

Moovweb Platform - Other Mobile Development

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