Mendix vs Neptune

Overview

Mendix

Stacks41

Followers56

Votes0

GitHub Stars160

Forks754

Neptune

Stacks16

Followers38

Votes2

Mendix vs Neptune: What are the differences?

Development Approach: Mendix follows a low-code approach, enabling users to visually create applications by dragging and dropping elements into place, while Neptune uses a code-first approach, providing a framework for developers to write code from scratch to build applications.
Integration Capabilities: Mendix offers pre-built connectors and integration tools for seamless integration with various systems and services, whereas Neptune requires custom development for integrations.
Customization Options: Mendix provides a range of out-of-the-box templates and modules for rapid development, whereas Neptune allows for deep customization and flexibility in design and development.
User Interface: Mendix offers a user-friendly interface for building applications, suitable for non-technical users, while Neptune requires a higher level of technical expertise for development.
Deployment Options: Mendix provides cloud-based deployment through its platform, offering scalability and ease of management, whereas Neptune offers flexibility to deploy applications on various infrastructures such as on-premise or cloud.
Community and Support: Mendix has a large and active community of users and developers for support and collaboration, while Neptune has a smaller community but provides dedicated support for its users.

In Summary, Mendix and Neptune differ in their development approach, integration capabilities, customization options, user interface, deployment options, and community support.

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CLI (Node.js)

Manual

Detailed Comparison

Mendix	Neptune
It is a low-code software platform. It provides tools to build, test, deploy and iterate applications.	It brings organization and collaboration to data science projects. All the experiement-related objects are backed-up and organized ready to be analyzed, reproduced and shared with others. Works with all common technologies and integrates with other tools.
Centralized App Governance; Drag & Drop Forms Builder; Enterprise Integration; Model-Driven Development; Multi-Channel, Multi-Device; Public/Private App Stores.	Experiment tracking; Experiment versioning; Experiment comparison; Experiment monitoring; Experiment sharing; Notebook versioning
Statistics
GitHub Stars 160	GitHub Stars -
GitHub Forks 754	GitHub Forks -
Stacks 41	Stacks 16
Followers 56	Followers 38
Votes 0	Votes 2
Pros & Cons
No community feedback yet	Pros 1 Supports both gremlin and openCypher query languages 1 Aws managed services Cons 1 Doesn't have much community support 1 Doesn't have proper clients for different lanuages 1 Doesn't have much support for openCypher clients
Integrations
Jira Swagger Inspector GitHub Confluence Webex Mandrill	PyTorch Keras R Language MLflow Matplotlib

What are some alternatives to Mendix, Neptune?

Parse

With Parse, you can add a scalable and powerful backend in minutes and launch a full-featured app in record time without ever worrying about server management. We offer push notifications, social integration, data storage, and the ability to add rich custom logic to your app’s backend with Cloud Code.

TensorFlow

TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.

built.io

Built.io Backend is an mBaaS that allows you to avoid designing, building, and supporting a custom backend for your mobile & web applications. Enterprises can dramatically reduce cost, lower risk and accelerate time-to-market for apps.

scikit-learn

scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.

PyTorch

PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.

Appcelerator

Appcelerator is the first mobile platform to combine the flexibility of open source development technologies with the power of cloud services.

Keras

Deep Learning library for Python. Convnets, recurrent neural networks, and more. Runs on TensorFlow or Theano. https://keras.io/

DreamFactory

DreamFactory is an open source REST API backend for mobile, web, and IoT applications. It provides RESTful web services with pre-built connectors to SQL, NoSQL, file storage systems, and web services. It's secure, reusable, and offers live API documentation.

Kubeflow

The Kubeflow project is dedicated to making Machine Learning on Kubernetes easy, portable and scalable by providing a straightforward way for spinning up best of breed OSS solutions.

TensorFlow.js

Use flexible and intuitive APIs to build and train models from scratch using the low-level JavaScript linear algebra library or the high-level layers API

Related Comparisons

Mendix vs Neptune: What are the differences?

Development Approach: Mendix follows a low-code approach, enabling users to visually create applications by dragging and dropping elements into place, while Neptune uses a code-first approach, providing a framework for developers to write code from scratch to build applications.
Integration Capabilities: Mendix offers pre-built connectors and integration tools for seamless integration with various systems and services, whereas Neptune requires custom development for integrations.
Customization Options: Mendix provides a range of out-of-the-box templates and modules for rapid development, whereas Neptune allows for deep customization and flexibility in design and development.
User Interface: Mendix offers a user-friendly interface for building applications, suitable for non-technical users, while Neptune requires a higher level of technical expertise for development.
Deployment Options: Mendix provides cloud-based deployment through its platform, offering scalability and ease of management, whereas Neptune offers flexibility to deploy applications on various infrastructures such as on-premise or cloud.
Community and Support: Mendix has a large and active community of users and developers for support and collaboration, while Neptune has a smaller community but provides dedicated support for its users.

In Summary, Mendix and Neptune differ in their development approach, integration capabilities, customization options, user interface, deployment options, and community support.

Mendix vs Neptune

Overview