Developing Interactive Charts with Chart.js for Websites

Why should you entrust interactive charts to us?

While developing an analytics dashboard for an e-commerce client, we ran into a typical problem: D3.js charts were eating up 2 seconds of LCP and didn't respond on mobile devices. We rewrote them with Chart.js — LCP dropped to 0.8 s, and responsiveness worked out of the box.

Here's how we implement interactive Chart.js charts in projects, and why it's more cost-effective than custom-built solutions.

What problems Chart.js solves

Heavy bundle. D3.js weighs 250+ KB, while Chart.js with react-chartjs-2 is only 60 KB gzip. This is critical for Core Web Vitals: smaller size = lower TTI and LCP. We reduce LCP by 40% compared to D3.js.

Customization complexity. Out-of-the-box standard charts rarely fit a brand. Chart.js lets you register custom scales, plugins, and tooltip callbacks without rewriting the engine.

Lack of interactivity. Clients want to click on a column and see the details, hover the cursor — and get a tooltip with formatted data. Chart.js supports onClick, onHover, and custom plugins "out of the box".

Responsiveness for mobile. By default, charts scale to fit the container, and at narrow widths they hide extra labels and the legend.

How we integrate Chart.js into a project

Choosing the version and modular registration

We use Chart.js v4 (4.10+). We register only the necessary modules — this reduces the bundle by another 10-20%.

import { Chart, LineController, LineElement, PointElement, LinearScale, CategoryScale } from 'chart.js';
Chart.register(LineController, LineElement, PointElement, LinearScale, CategoryScale);

Optimizing re-renders in React

The chart re-renders every time the parent updates. We use React.memo and useMemo for the data:

const MemoLineChart = React.memo(Line);
function Dashboard({ data }) {
  const chartData = useMemo(() => transformData(data), [data]);
  return <MemoLineChart data={chartData} options={options} />;
}

Custom plugins for business logic

We write "now" line plugins, annotations, and horizontal target lines. An example is below.

Typing data with TypeScript

All datasets are strictly typed, which reduces runtime bugs.

interface RevenueData { date: string; revenue: number; forecast: number; }

Library comparison

For 80% of business tasks, Chart.js wins: faster to develop, lighter, easier to maintain. We keep D3.js for custom visualizations like graphs or SanKey.

Work Process

1. Data analytics. We determine which metrics will be on the charts, the update frequency, and the data format.
2. Prototyping. In Figma, we draw mockups — the layout of charts, interactions, and loading states.
3. Component development. We create reusable components with Chart.js and cover them with unit tests.
4. API integration. If data comes from a server, we set up caching and prefetch.
5. Testing. We test on 3 browsers (Chrome, Firefox, Safari) and mobile devices.
6. Deployment. We enable code-splitting (charts load asynchronously) and bug monitoring via Sentry.

What is included in the work

• Source code of components in React/Next.js with TypeScript
• Documentation on setup and integration (in README or Storybook format)
• Access to the repository with commit history
• Training of the customer's team (1-2 sessions of one hour each)
• 1-month warranty for fixing hidden bugs

Common mistakes during implementation

• Forgetting to register all required modules — the chart does not render without errors.
• Redrawing the chart on every parent state change — use React.memo and useMemo.
• Not formatting tooltips — users see raw numbers.
• Not checking responsiveness on mobile — on narrow screens the text overlaps.

Why is Chart.js better than a custom-built solution?

A custom-built Canvas chart takes 2-3 weeks and cannot compare in richness of features. Chart.js provides animation, tooltips, a legend, and scaling in a couple of days. In 9 out of 10 cases, this is the fastest path to a working dashboard.

How to avoid repeated chart re-renders?

Use React.memo and pass data through useMemo. You can also extract the chart into a separate component with its own data subscription.

Timeline and cost

Timeline — from 3 to 10 days depending on the number of chart types and the complexity of interactivity. The cost is calculated individually after the brief. We lock it in at the stage of signing the technical specification — no unexpected extra charges.

Write to us to assess the complexity of your project. Get a consultation on Chart.js integration and Core Web Vitals optimization.

We have been working in data visualization for over 5 years and have delivered 30+ projects with interactive charts. Experience with dashboards for e-commerce, finance, and logistics.

Chart.js — official documentation.