Comparison of ECharts with other visualization libraries

Comparison between ECharts and D3.js

D3.js is a data-driven document manipulation library that offers extremely high flexibility. In contrast, ECharts leans more toward an out-of-the-box solution. D3.js requires manual handling of DOM elements and SVG rendering, while ECharts automates these tasks through declarative configurations.

// D3.js drawing a simple bar chart  
const data = [30, 70, 110, 90, 150];  
d3.select("#chart")  
  .selectAll("div")  
  .data(data)  
  .enter()  
  .append("div")  
  .style("height", d => `${d}px`);  

// ECharts achieving the same effect  
option = {  
  xAxis: { type: 'category', data: ['A', 'B', 'C', 'D', 'E'] },  
  yAxis: { type: 'value' },  
  series: [{ data: data, type: 'bar' }]  
};  

D3.js is suitable for scenarios requiring full customization, such as specialized data visualization art projects. ECharts, on the other hand, is more efficient in conventional business chart development, with built-in interactive features like zooming and tooltips.

Comparison between ECharts and Highcharts

Highcharts is a typical representative of commercial visualization libraries and is the closest to ECharts in terms of functionality and positioning. Both offer rich chart types and configuration options, but there are key differences:

1. Licensing: Highcharts is free for non-commercial use but requires a paid license for commercial projects; ECharts adopts the Apache 2.0 open-source license.
2. Chinese Documentation: ECharts is developed by the Baidu team, so its Chinese documentation is more comprehensive.
3. Extensibility: ECharts provides more flexible extension mechanisms, supporting custom series and components.

// Highcharts bar chart configuration  
Highcharts.chart('container', {  
  chart: { type: 'bar' },  
  series: [{ data: [1, 2, 3, 4, 5] }]  
});  

// ECharts achieving the same effect  
option = {  
  series: [{ type: 'bar', data: [1, 2, 3, 4, 5] }]  
};  

In terms of mobile adaptation, ECharts excels with its responsive design, offering finer touch interaction support.

Comparison between ECharts and Chart.js

Chart.js is a lightweight Canvas chart library suitable for quick implementation in simple scenarios. Compared to ECharts:

• Size: Chart.js is about 60KB when compressed, while the full version of ECharts is around 700KB.
• Features: ECharts supports 30+ chart types, whereas Chart.js only offers 8 basic types.
• Animations: ECharts provides richer and smoother animation effects.

// Chart.js pie chart example  
new Chart(ctx, {  
  type: 'pie',  
  data: {  
    labels: ['Red', 'Blue'],  
    datasets: [{ data: [30, 70] }]  
  }  
});  

// ECharts pie chart configuration  
option = {  
  series: [{  
    type: 'pie',  
    data: [  
      { value: 30, name: 'Red' },  
      { value: 70, name: 'Blue' }  
    ]  
  }]  
};  

For scenarios requiring quick embedding of simple charts, Chart.js is more suitable. When complex interactions and rich visual effects are needed, ECharts is the better choice.

Comparison between ECharts and Tableau

Tableau is a professional data analysis tool, belonging to a different category from programming libraries like ECharts:

1. Usage: Tableau operates via a GUI, while ECharts requires coding.
2. Data Processing: Tableau has built-in data processing capabilities, whereas ECharts needs to be paired with other libraries.
3. Deployment Cost: Tableau requires server licensing, while ECharts can be freely integrated into web applications.

// ECharts heatmap implementation  
option = {  
  tooltip: {},  
  visualMap: { min: 0, max: 10 },  
  xAxis: { type: 'category' },  
  yAxis: { type: 'category' },  
  series: {  
    type: 'heatmap',  
    data: [[0,0,5], [1,1,2], ...]  
  }  
};  

For non-technical users requiring deep data analysis, Tableau is more suitable. When developing data visualization applications, ECharts offers greater flexibility.

Comparison between ECharts and AntV

AntV is a visualization solution launched by Ant Group, consisting of multiple sub-products. The main differences from ECharts include:

• Architecture: AntV adopts a layered architecture (G2, G6, etc.), while ECharts has a unified architecture.
• Graph Analysis: AntV's G6 excels in graph relationship analysis.
• Mobile Optimization: AntV's F2 is specifically optimized for mobile.

// G2 line chart implementation  
const chart = new G2.Chart({  
  container: 'container',  
  autoFit: true  
});  
chart.line().position('x*y').data(data);  
chart.render();  

// ECharts line chart  
option = {  
  xAxis: { type: 'category' },  
  yAxis: { type: 'value' },  
  series: [{ type: 'line', data: yData }]  
};  

In BI system development, AntV's chart linkage capabilities are stronger. ECharts performs better in dynamic data updates and large dataset rendering.

Comparison between ECharts and Plotly

Plotly is built on D3.js and stack.gl, belonging to the same category of open-source visualization libraries as ECharts:

1. Language Support: Plotly supports backend languages like Python/R, while ECharts focuses on JavaScript.
2. 3D Visualization: Plotly's 3D chart support is more mature.
3. Community: ECharts has a more active Chinese community.

// Plotly scatter plot  
Plotly.newPlot('graph', [{  
  x: [1,2,3],  
  y: [3,2,1],  
  mode: 'markers'  
}]);  

// ECharts scatter plot  
option = {  
  xAxis: {},  
  yAxis: {},  
  series: {  
    type: 'scatter',  
    data: [[1,3], [2,2], [3,1]]  
  }  
};  

For scientific computing and academic research scenarios, Plotly may be more suitable. In commercial reporting and dashboard development, ECharts' configuration approach aligns better with developer habits.

Comparison between ECharts and Google Charts

Google Charts is a free chart service provided by Google. The main differences from ECharts include:

• Dependency: Google Charts requires an internet connection to load, while ECharts can be used offline.
• Customization: ECharts offers stronger styling customization capabilities.
• Maps: ECharts has more detailed built-in maps of China.

// Google Charts bar chart  
google.charts.load('current', {packages: ['corechart']});  
google.charts.setOnLoadCallback(() => {  
  const data = google.visualization.arrayToDataTable([  
    ['City', 'Population'],  
    ['Beijing', 2154],  
    ['Shanghai', 2424]  
  ]);  
  new google.visualization.ColumnChart(document.getElementById('chart'));  
});  

// ECharts implementation  
option = {  
  dataset: { source: [ ['Beijing',2154], ['Shanghai',2424] ] },  
  xAxis: { type: 'category' },  
  yAxis: {},  
  series: [{ type: 'bar' }]  
};  

In scenarios requiring completely offline environments or deep customization of China maps, ECharts has clear advantages. For quick integration into Google ecosystem applications, Google Charts may be more convenient.