Pros of Vega

• More mature and established project with a larger community and ecosystem
• Offers greater flexibility and customization options for creating complex visualizations
• Supports a wider range of chart types and data transformations

Cons of Vega

• Steeper learning curve due to its more comprehensive feature set
• Requires more code and configuration for basic visualizations
• Less focus on 3D visualizations compared to SandDance

Code Comparison

SandDance:

const view = await vega.embed('#vis', {
  $schema: 'https://vega.github.io/schema/vega-lite/v4.json',
  data: { values: data },
  mark: 'point',
  encoding: { x: { field: 'x' }, y: { field: 'y' } }
});

Vega:

const spec = {
  $schema: 'https://vega.github.io/schema/vega/v5.json',
  width: 400, height: 200,
  data: [{ name: 'table', values: data }],
  marks: [{ type: 'symbol', from: { data: 'table' },
    encode: { enter: { x: { field: 'x' }, y: { field: 'y' } } }
  }]
};
const view = new vega.View(vega.parse(spec)).render('#vis');

Both libraries use declarative JSON specifications to define visualizations, but Vega requires more detailed configuration for similar results. SandDance focuses on simplicity for 3D visualizations, while Vega offers more control and flexibility for a wider range of chart types.

Pros of Plotly.js

• Extensive chart types and customization options
• Large community and ecosystem with numerous extensions
• Well-documented API with interactive examples

Cons of Plotly.js

• Steeper learning curve for complex visualizations
• Larger file size, which may impact page load times
• Can be resource-intensive for large datasets

Code Comparison

SandDance:

import * as SandDance from "@msrvida/sanddance-react";

const view = new SandDance.Viewer(element);
view.render({
  data: myData,
  chart: "scatterplot",
  columns: { x: "sales", y: "profit" }
});

Plotly.js:

import Plotly from 'plotly.js-dist';

Plotly.newPlot('myDiv', [{
  x: [1, 2, 3, 4],
  y: [10, 15, 13, 17],
  type: 'scatter'
}]);

SandDance focuses on unit visualizations and offers a more declarative API, while Plotly.js provides a wider range of chart types with a more imperative approach. Plotly.js excels in traditional charting scenarios, whereas SandDance shines in exploratory data analysis with its unique unit visualization concept.

Pros of D3

• Highly flexible and customizable for creating a wide range of data visualizations
• Large and active community with extensive documentation and examples
• Powerful data binding and manipulation capabilities

Cons of D3

• Steeper learning curve, especially for complex visualizations
• Requires more low-level coding compared to higher-level libraries
• Performance can be an issue with large datasets or complex animations

Code Comparison

SandDance:

const view = await vega.embed('#vis', {
  $schema: 'https://vega.github.io/schema/vega-lite/v4.json',
  data: { values: data },
  mark: 'point',
  encoding: { x: { field: 'x', type: 'quantitative' }, y: { field: 'y', type: 'quantitative' } }
});

D3:

const svg = d3.select('#vis')
  .append('svg')
  .attr('width', width)
  .attr('height', height);

svg.selectAll('circle')
  .data(data)
  .enter()
  .append('circle')
  .attr('cx', d => xScale(d.x))
  .attr('cy', d => yScale(d.y))
  .attr('r', 5);

SandDance provides a higher-level abstraction for creating visualizations, while D3 offers more granular control over the rendering process. SandDance's code is more declarative, whereas D3 requires more imperative programming to achieve similar results.

Pros of ECharts

• More comprehensive and versatile, offering a wider range of chart types and visualization options
• Larger community and ecosystem, with extensive documentation and third-party extensions
• Better performance for handling large datasets and rendering complex visualizations

Cons of ECharts

• Steeper learning curve due to its extensive API and configuration options
• Larger file size, which may impact load times for web applications
• Less focus on specific data exploration and analysis features compared to SandDance

Code Comparison

SandDance:

import * as SandDance from "@msrvida/sanddance-react";

<SandDance.Viewer
  data={myData}
  insight={{
    chart: "scatterplot",
    columns: { x: "sales", y: "profit" }
  }}
/>

ECharts:

import * as echarts from 'echarts';

const chart = echarts.init(document.getElementById('chart'));
chart.setOption({
  xAxis: { type: 'value' },
  yAxis: { type: 'value' },
  series: [{
    type: 'scatter',
    data: myData.map(item => [item.sales, item.profit])
  }]
});

Pros of nivo

• Offers a wider variety of chart types and visualizations
• More customizable and flexible for complex data visualization needs
• Active development with frequent updates and new features

Cons of nivo

• Steeper learning curve due to its extensive API and options
• May require more setup and configuration for basic use cases

Code Comparison

SandDance:

import * as React from 'react';
import { SandDance } from '@msrvida/sanddance-react';

const App = () => (
  <SandDance data={myData} />
);

nivo:

import { ResponsiveLine } from '@nivo/line'

const MyChart = () => (
  <ResponsiveLine
    data={data}
    margin={{ top: 50, right: 110, bottom: 50, left: 60 }}
    xScale={{ type: 'point' }}
    yScale={{ type: 'linear', min: 'auto', max: 'auto', stacked: true, reverse: false }}
  />
)

SandDance provides a simpler API for quick visualizations, while nivo offers more granular control over chart properties and appearance. nivo's code tends to be more verbose but allows for greater customization.

Pros of deck.gl

• Highly performant for large datasets, capable of rendering millions of data points
• Extensive ecosystem with many pre-built layers and extensions
• Strong integration with mapping libraries like Mapbox GL

Cons of deck.gl

• Steeper learning curve due to its comprehensive API and features
• Requires more setup and configuration for basic visualizations

Code Comparison

SandDance:

var viewer = new SandDance.Viewer(element);
viewer.render({
    data: myData,
    chart: 'scatterplot',
    columns: { x: 'sales', y: 'profit' }
});

deck.gl:

const layer = new ScatterplotLayer({
    data: myData,
    getPosition: d => [d.sales, d.profit],
    getRadius: 1,
    pickable: true
});
new Deck({ layers: [layer] });

Summary

While SandDance offers a more user-friendly approach for quick data exploration and visualization, deck.gl provides greater flexibility and performance for complex, large-scale data visualizations. SandDance excels in ease of use and rapid prototyping, whereas deck.gl shines in customization and handling massive datasets, particularly in geospatial contexts.