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NetworkX VS MUI X Data Grid

Compare NetworkX VS MUI X Data Grid and see what are their differences

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Turn SQL Data into Decisions. Build professional dashboards and data visualizations without technical expertise. Easily embed analytics anywhere, receive automated alerts, and discover AI-powered insights all through a straightforward interface. featured
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NetworkX logo NetworkX

NetworkX is a Python language software package for the creation, manipulation, and study of the...

MUI X Data Grid logo MUI X Data Grid

A fast and extensible React data table and React data grid, with filtering, sorting, aggregation, and more.
  • NetworkX Landing page
    Landing page //
    2023-09-14
Not present

A fast and extensible React data table and React data grid, with filtering, sorting, aggregation, and more.

The MUI X Data Grid is a TypeScript-based React component that presents information in a structured format of rows and columns. It provides developers with an intuitive API for implementing complex use cases; and end users with a smooth experience for manipulating an unlimited set of data.

The Grid's theming features are designed to be frictionless when integrating with Material UI and other MUI X components, but it can also stand on its own and be customized to meet the needs of any design system.

The Data Grid is open-core: The Community version is MIT-licensed and free forever, while more advanced features require a Pro or Premium commercial license. See MUI X Licensing for complete details.

NetworkX features and specs

  • Ease of Use
    NetworkX provides a simple and intuitive API that makes it easy for both novices and experienced users to create, manipulate, and study the structure and dynamics of complex networks.
  • Comprehensive Documentation
    The library is well-documented with a vast number of examples and tutorials, aiding users in understanding and applying the features effectively.
  • Rich Functionality
    NetworkX offers numerous built-in functions to analyze network properties, perform algorithms like shortest path and clustering, and handle various graph types such as directed, undirected, and multigraphs.
  • Integration with Python Ecosystem
    Being a Python library, NetworkX integrates seamlessly with other scientific computing libraries like NumPy, SciPy, and Matplotlib, allowing for extensive data analysis and visualization.
  • Active Community
    NetworkX's active community of users and developers means continuous improvements and updates, as well as a wealth of shared knowledge and code to draw upon.

Possible disadvantages of NetworkX

  • Performance Limitations
    NetworkX may suffer from performance issues with extremely large graphs due to its in-memory data storage and Python's inherent single-threaded execution, making it less suitable for handling very large-scale networks.
  • Lack of Parallel Processing
    NetworkX does not natively support parallel processing within its operations, which can be a drawback when working with complex computations or very large graphs.
  • Memory Consumption
    Graphs and network data structures in NetworkX may consume a substantial amount of memory, especially with large datasets, potentially leading to inefficiencies.
  • Visualization Limitations
    While NetworkX provides basic plotting capabilities, for more advanced and interactive visualizations, additional libraries like Matplotlib or Plotly might be needed.
  • Scalability Constraints
    The library is not designed to work efficiently with very large networks compared to other frameworks specialized for scalability, such as Graph-tool or igraph.

MUI X Data Grid features and specs

  • Rich Component Library
    MUI X offers a wide range of advanced components such as data grids, date pickers, and charts, which enhance the user interface and experience of complex applications.
  • Customizability
    The components in MUI X are highly customizable, allowing developers to style and configure them according to their specific application needs.
  • Performance
    MUI X components are designed with performance in mind, ensuring that even complex components like data grids run smoothly, which is crucial for large datasets.
  • Integration with Material UI
    MUI X seamlessly integrates with Material UI, providing a consistent design system and allowing developers to use both basic and advanced components together.
  • Community and documentation
    MUI X benefits from robust community support and comprehensive documentation, making it easier for developers to find solutions and best practices.

Possible disadvantages of MUI X Data Grid

  • Cost for Pro Components
    While MUI X offers some free components, access to the full suite of advanced components requires a subscription, which might be a limiting factor for startups or individual developers.
  • Complexity
    The complexity of the components can lead to a steeper learning curve, requiring more time and effort for new developers to get acquainted with the library.
  • Dependency on React
    MUI X is built on React, meaning it's not suitable for projects that use different frameworks, potentially limiting its adoption across diverse tech stacks.
  • Overhead for Small Projects
    For smaller projects, the extensive feature set of MUI X might be overkill, introducing unnecessary overhead in development and build processes.

NetworkX videos

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Directed Network Analysis - Simulating a Social Network Using Networkx in Python - Tutorial 28

MUI X Data Grid videos

No MUI X Data Grid videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to NetworkX and MUI X Data Grid)

NetworkX

MUI X Data Grid

Graph Databases
100 100%
Graph Databases
0% 0
Data Grid
0 0%
Data Grid
100% 100
Databases
100 100%
Databases
0% 0
Design Tools
0 0%
Design 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 NetworkX and MUI X Data Grid

NetworkX Reviews

We have no reviews of NetworkX yet.
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MUI X Data Grid Reviews

  1. oliviertassinari
Using AG Grid in React: Guide and alternatives
In this guide, we introduced the basic functionalities of the ag-grid-react library and demonstrated how to use AG Grid to build and style a data grid in a React app. To compare alternatives to AG Grid, also built a similar data grid in TanStack Table, Glide Data Grid, and MUI Data Grid. Each library has a unique set of features and tradeoffs, so it’s important to choose the...
Source: blog.logrocket.com
The Best React Data Grid/Table Libraries with Material Design in 2023 - MRT Blog
AG Grid is also in a similar situation as MUI X DataGrid, where some of the features are only available in the paid Enterprise version. However, the free version is still very feature-rich and will take you very far in most projects. AG Grid is one of the few high-quality OSS projects out there where it is probably worth every penny to pay for the Enterprise version if you...
Source: www.material-react-table.com

Social recommendations and mentions

Based on our record, NetworkX seems to be more popular. It has been mentiond 35 times since March 2021. 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.

NetworkX mentions (35)

  • Representing Graphs in PostgreSQL
    If you are interested in the subject, also take a look at NetworkDisk[1] which enable users of NetworkX[2] which maps graphs to databases. [1] https://networkdisk.inria.fr/ [2] https://networkx.org/. - Source: Hacker News / 4 months ago
  • Build the dependency graph of your BigQuery pipelines at no cost: a Python implementation
    In the project we used Python lib networkx and a DiGraph object (Direct Graph). To detect a table reference in a Query, we use sqlglot, a SQL parser (among other things) that works well with Bigquery. - Source: dev.to / over 1 year ago
  • Custom libraries and utility tools for challenges
    If you program in Python, can use NetworkX for that. But it's probably a good idea to implement the basic algorithms yourself at least one time. Source: over 1 year ago
  • Google open-sources their graph mining library
    For those wanting to play with graphs and ML I was browsing the arangodb docs recently and I saw that it includes integrations to various graph libraries and machine learning frameworks [1]. I also saw a few jupyter notebooks dealing with machine learning from graphs [2]. Integrations include: * NetworkX -- https://networkx.org/ * DeepGraphLibrary -- https://www.dgl.ai/ * cuGraph (Rapids.ai Graph) --... - Source: Hacker News / over 1 year ago
  • org-roam-pygraph: Build a graph of your org-roam collection for use in Python
    Org-roam-ui is a great interactive visualization tool, but its main use is visualization. The hope of this library is that it could be part of a larger graph analysis pipeline. The demo provides an example graph visualization, but what you choose to do with the resulting graph certainly isn't limited to that. See for example networkx. Source: about 2 years ago
View more

MUI X Data Grid mentions (0)

We have not tracked any mentions of MUI X Data Grid yet. Tracking of MUI X Data Grid recommendations started around Jun 2023.

What are some alternatives?

When comparing NetworkX and MUI X Data Grid, you can also consider the following products

neo4j - Meet Neo4j: The graph database platform powering today's mission-critical enterprise applications, including artificial intelligence, fraud detection and recommendations.

AG Grid - The best HTML5 datagrid in the world

RedisGraph - A high-performance graph database implemented as a Redis module.

TanStack Table - Headless UI for building powerful tables & datagrids with TS/JS, React, Solid, Svelte and Vue

Azure Cosmos DB - NoSQL JSON database for rapid, iterative app development.

material-table - React data table component that is based on material-ui

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