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Material React Table VS NLP-API

Compare Material React Table VS NLP-API and see what are their differences

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Contents:
  1. » Base Details
  2. » Reviews
  3. » Alternatives

Material React Table logo Material React Table

Material React Table, a fully featured Material UI V5 implementation of TanStack React Table V8. Written from the ground up in TypeScript.

NLP-API logo NLP-API

Natural Language Processing tools REST API
  • Material React Table Landing page
    Landing page //
    2023-09-03
  • NLP-API Landing page
    Landing page //
    2023-03-15

Category Popularity

0-100% (relative to Material React Table and NLP-API)

Material React Table

NLP-API

Design Tools
100 100%
Design Tools
0% 0
AI
0 0%
AI
100% 100
Data Grid
100 100%
Data Grid
0% 0
Developer Tools
0 0%
Developer 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 Material React Table and NLP-API

Material React Table Reviews

The Best React Data Grid/Table Libraries with Material Design in 2023 - MRT Blog
The final library on this list is Material React Table. This is a relatively new library that was first released in September 2022. Unlike the two previously mentioned libraries, Material React Table is 100% free to use with the MIT license. It is also built directly on top of Material UI v5 and exclusively uses Material UI components under the hood, so it will fit right in...
Source: www.material-react-table.com

NLP-API Reviews

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What are some alternatives?

When comparing Material React Table and NLP-API, you can also consider the following products

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

Texti.app - AI that lives in your browser!

AG Grid - The best HTML5 datagrid in the world

Loqui-Ai - Loqui-Ai is an AI language learning companion designed to help people interact with their Target language.

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

Kern AI refinery - Algorithms aren’t the bottlenecks. It’s data. Develop data to get better quality in shorter time with refinery. Build your AI training data in hours, not months.

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