What is amCharts and what are its top alternatives?
amCharts is a powerful JavaScript charting library that allows users to create interactive and visually appealing charts and graphs for web applications. Some key features of amCharts include a wide range of chart types, built-in themes for customization, multi-language support, extensive documentation, and compatibility with various platforms. However, a limitation of amCharts is that the free version has limited features and a watermark on the charts.
- Highcharts: Highcharts is a popular JavaScript charting library that offers a wide range of chart types, interactive features, and customization options. Pros include extensive documentation, easy integration with various frameworks, and strong community support. Cons compared to amCharts include a higher cost for commercial use and being less feature-rich in the free version.
- D3.js: D3.js is a powerful data visualization library that provides great flexibility in creating customizable and complex charts. Pros include its ability to handle large datasets and its strong community support. Cons compared to amCharts include a steeper learning curve and more complex implementation.
- Chart.js: Chart.js is a lightweight charting library that offers simple and responsive charts with various customization options. Pros include easy integration, good performance, and a simple API. Cons compared to amCharts include a limited range of chart types and less advanced features.
- Google Charts: Google Charts is a free charting library from Google that offers a variety of chart types and styling options. Pros include easy integration with Google services, good performance, and a wide range of chart types. Cons compared to amCharts include limited customization options and less advanced features.
- Plotly: Plotly is a JavaScript graphing library that offers interactive charts, real-time data visualization, and support for various programming languages. Pros include its ease of use, extensive documentation, and advanced features like subplots and animations. Cons compared to amCharts include a more limited range of chart types and some advanced features being available only in paid versions.
- FusionCharts: FusionCharts is a comprehensive charting library that offers a wide range of interactive charts, maps, and dashboards. Pros include extensive chart customization options, support for real-time data, and good performance. Cons compared to amCharts include a higher cost for commercial licenses and a more complex API.
- ApexCharts: ApexCharts is a modern JavaScript charting library that offers a simple API, responsive charts, and support for streaming data. Pros include easy integration with front-end frameworks, good performance, and customization options. Cons compared to amCharts include a more limited range of chart types and a smaller community.
- ECharts: ECharts is a powerful charting library from Apache that offers a wide range of chart types, animation support, and interactive features. Pros include good performance, extensive documentation, and support for big data visualization. Cons compared to amCharts include a more complex configuration and customization process.
- Toast UI Chart: Toast UI Chart is an open-source charting library that offers various chart types, customization options, and responsive design. Pros include ease of use, good performance, and support for both vertical and horizontal layouts. Cons compared to amCharts include a smaller community and a less extensive range of chart types.
- ZingChart: ZingChart is a charting library that offers a wide range of chart types, tool integrations, and interactive features like zooming and panning. Pros include good performance, extensive documentation, and the ability to create complex dashboards. Cons compared to amCharts include a less intuitive API and a higher cost for commercial licenses.
Top Alternatives to amCharts
- Highcharts
Highcharts currently supports line, spline, area, areaspline, column, bar, pie, scatter, angular gauges, arearange, areasplinerange, columnrange, bubble, box plot, error bars, funnel, waterfall and polar chart types. ...
- D3.js
It is a JavaScript library for manipulating documents based on data. Emphasises on web standards gives you the full capabilities of modern browsers without tying yourself to a proprietary framework. ...
- Google Charts
It is an interactive Web service that creates graphical charts from user-supplied information. The user supplies data and a formatting specification expressed in JavaScript embedded in a Web page; in response the service sends an image of the chart. ...
- FusionCharts
It is the most comprehensive JavaScript charting library, with over 100+ charts and 2000+ maps. Integrated with all popular JavaScript frameworks and server-side programming languages. Create interactive JavaScript charts for your web and enterprise applications. ...
- Plotly.js
It is a standalone Javascript data visualization library, and it also powers the Python and R modules named plotly in those respective ecosystems (referred to as Plotly.py and Plotly.R). It can be used to produce dozens of chart types and visualizations, including statistical charts, 3D graphs, scientific charts, SVG and tile maps, financial charts and more. ...
- ECharts
It is an open source visualization library implemented in JavaScript, runs smoothly on PCs and mobile devices, and is compatible with most current browsers. ...
- Victory
A collection of composable React components for building interactive data visualizations. ...
- JavaScript
JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles. ...
amCharts alternatives & related posts
Highcharts
- Low learning curve and powerful34
- Multiple chart types such as pie, bar, line and others17
- Responsive charts13
- Handles everything you throw at it9
- Extremely easy-to-parse documentation8
- Built-in export chart as-is to image file5
- Easy to customize color scheme and palettes5
- Export on server side, can be used in email1
- Expensive9
related Highcharts posts
Here is my stack on #Visualization. @FusionCharts and Highcharts are easy to use but only free for non-commercial. Chart.js and Plotly are two lovely tools for commercial use under the MIT license. And D3.js would be my last choice only if a complex customized plot is needed.
- Beautiful visualizations195
- Svg103
- Data-driven92
- Large set of examples81
- Data-driven documents61
- Visualization components24
- Transitions20
- Dynamic properties18
- Plugins16
- Transformation11
- Makes data interactive7
- Open Source4
- Enter and Exit4
- Components4
- Exhaustive3
- Backed by the new york times3
- Easy and beautiful2
- Highly customizable1
- Awesome Community Support1
- Simple elegance1
- Templates, force template1
- Angular 41
- Beginners cant understand at all11
- Complex syntax6
related D3.js posts
We use Plotly (just their open source stuff) for Zulip's user-facing and admin-facing statistics graphs because it's a reasonably well-designed JavaScript graphing library.
If you've tried using D3.js, it's a pretty poor developer experience, and that translates to spending a bunch of time getting the graphs one wants even for things that are conceptually pretty basic. Plotly isn't amazing (it's decent), but it's way better than than D3 unless you have very specialized needs.
Hi,
I am looking at integrating a charting library in my React frontend that allows me to create appealing and interactive charts. I have basic familiarity with ApexCharts with React but have also read about D3.js charts and it seems a much more involved integration. Can someone please share their experience across the two libraries on the following dimensions:
- Amount of work needed for integration
- Amount of work or ease for creating new charts in either of the libraries.
Regards
Amit
related Google Charts posts
- Not free1
related FusionCharts posts
- Bindings to popular languages like Python, Node, R, etc16
- Integrated zoom and filter-out tools in charts and maps10
- Great support for complex and multiple axes9
- Powerful out-of-the-box featureset8
- Beautiful visualizations6
- Active user base4
- Impressive support for webgl 3D charts4
- Charts are easy to share with a cloud account3
- Webgl chart types are extremely performant3
- Interactive charts2
- Easy to use online editor for creating plotly.js charts2
- Publication quality image export2
- Terrible document18
related Plotly.js posts
We use Plotly (just their open source stuff) for Zulip's user-facing and admin-facing statistics graphs because it's a reasonably well-designed JavaScript graphing library.
If you've tried using D3.js, it's a pretty poor developer experience, and that translates to spending a bunch of time getting the graphs one wants even for things that are conceptually pretty basic. Plotly isn't amazing (it's decent), but it's way better than than D3 unless you have very specialized needs.
Here is my stack on #Visualization. @FusionCharts and Highcharts are easy to use but only free for non-commercial. Chart.js and Plotly are two lovely tools for commercial use under the MIT license. And D3.js would be my last choice only if a complex customized plot is needed.
- East to implement7
- Smaller learning curve6
- Free to use5
- Vue Compatible4
- Very customizable3
- Angular compatible3
- React compatible2
- Support is in chinese2
related ECharts posts
related Victory posts
Server side
We decided to use Python for our backend because it is one of the industry standard languages for data analysis and machine learning. It also has a lot of support due to its large user base.
Web Server: We chose Flask because we want to keep our machine learning / data analysis and the web server in the same language. Flask is easy to use and we all have experience with it. Postman will be used for creating and testing APIs due to its convenience.
Machine Learning: We decided to go with PyTorch for machine learning since it is one of the most popular libraries. It is also known to have an easier learning curve than other popular libraries such as Tensorflow. This is important because our team lacks ML experience and learning the tool as fast as possible would increase productivity.
Data Analysis: Some common Python libraries will be used to analyze our data. These include NumPy, Pandas , and matplotlib. These tools combined will help us learn the properties and characteristics of our data. Jupyter notebook will be used to help organize the data analysis process, and improve the code readability.
Client side
UI: We decided to use React for the UI because it helps organize the data and variables of the application into components, making it very convenient to maintain our dashboard. Since React is one of the most popular front end frameworks right now, there will be a lot of support for it as well as a lot of potential new hires that are familiar with the framework. CSS 3 and HTML5 will be used for the basic styling and structure of the web app, as they are the most widely used front end languages.
State Management: We decided to use Redux to manage the state of the application since it works naturally to React. Our team also already has experience working with Redux which gave it a slight edge over the other state management libraries.
Data Visualization: We decided to use the React-based library Victory to visualize the data. They have very user friendly documentation on their official website which we find easy to learn from.
Cache
- Caching: We decided between Redis and memcached because they are two of the most popular open-source cache engines. We ultimately decided to use Redis to improve our web app performance mainly due to the extra functionalities it provides such as fine-tuning cache contents and durability.
Database
- Database: We decided to use a NoSQL database over a relational database because of its flexibility from not having a predefined schema. The user behavior analytics has to be flexible since the data we plan to store may change frequently. We decided on MongoDB because it is lightweight and we can easily host the database with MongoDB Atlas . Everyone on our team also has experience working with MongoDB.
Infrastructure
- Deployment: We decided to use Heroku over AWS, Azure, Google Cloud because it is free. Although there are advantages to the other cloud services, Heroku makes the most sense to our team because our primary goal is to build an MVP.
Other Tools
Communication Slack will be used as the primary source of communication. It provides all the features needed for basic discussions. In terms of more interactive meetings, Zoom will be used for its video calls and screen sharing capabilities.
Source Control The project will be stored on GitHub and all code changes will be done though pull requests. This will help us keep the codebase clean and make it easy to revert changes when we need to.
As a frontend engineer on the Algorithms & Analytics team at Stitch Fix, I work with data scientists to develop applications and visualizations to help our internal business partners make data-driven decisions. I envisioned a platform that would assist data scientists in the data exploration process, allowing them to visually explore and rapidly iterate through their assumptions, then share their insights with others. This would align with our team's philosophy of having engineers "deploy platforms, services, abstractions, and frameworks that allow the data scientists to conceive of, develop, and deploy their ideas with autonomy", and solve the pain of data exploration.
The final product, code-named Dora, is built with React, Redux.js and Victory, backed by Elasticsearch to enable fast and iterative data exploration, and uses Apache Spark to move data from our Amazon S3 data warehouse into the Elasticsearch cluster.
JavaScript
- Can be used on frontend/backend1.7K
- It's everywhere1.5K
- Lots of great frameworks1.2K
- Fast898
- Light weight745
- Flexible425
- You can't get a device today that doesn't run js392
- Non-blocking i/o286
- Ubiquitousness237
- Expressive191
- Extended functionality to web pages55
- Relatively easy language49
- Executed on the client side46
- Relatively fast to the end user30
- Pure Javascript25
- Functional programming21
- Async15
- Full-stack13
- Setup is easy12
- Future Language of The Web12
- Its everywhere12
- Because I love functions11
- JavaScript is the New PHP11
- Like it or not, JS is part of the web standard10
- Expansive community9
- Everyone use it9
- Can be used in backend, frontend and DB9
- Easy9
- Most Popular Language in the World8
- Powerful8
- Can be used both as frontend and backend as well8
- For the good parts8
- No need to use PHP8
- Easy to hire developers8
- Agile, packages simple to use7
- Love-hate relationship7
- Photoshop has 3 JS runtimes built in7
- Evolution of C7
- It's fun7
- Hard not to use7
- Versitile7
- Its fun and fast7
- Nice7
- Popularized Class-Less Architecture & Lambdas7
- Supports lambdas and closures7
- It let's me use Babel & Typescript6
- Can be used on frontend/backend/Mobile/create PRO Ui6
- 1.6K Can be used on frontend/backend6
- Client side JS uses the visitors CPU to save Server Res6
- Easy to make something6
- Clojurescript5
- Promise relationship5
- Stockholm Syndrome5
- Function expressions are useful for callbacks5
- Scope manipulation5
- Everywhere5
- Client processing5
- What to add5
- Because it is so simple and lightweight4
- Only Programming language on browser4
- Test1
- Hard to learn1
- Test21
- Not the best1
- Easy to understand1
- Subskill #41
- Easy to learn1
- Hard 彤0
- A constant moving target, too much churn22
- Horribly inconsistent20
- Javascript is the New PHP15
- No ability to monitor memory utilitization9
- Shows Zero output in case of ANY error8
- Thinks strange results are better than errors7
- Can be ugly6
- No GitHub3
- Slow2
- HORRIBLE DOCUMENTS, faulty code, repo has bugs0
related JavaScript posts
Oof. I have truly hated JavaScript for a long time. Like, for over twenty years now. Like, since the Clinton administration. It's always been a nightmare to deal with all of the aspects of that silly language.
But wowza, things have changed. Tooling is just way, way better. I'm primarily web-oriented, and using React and Apollo together the past few years really opened my eyes to building rich apps. And I deeply apologize for using the phrase rich apps; I don't think I've ever said such Enterprisey words before.
But yeah, things are different now. I still love Rails, and still use it for a lot of apps I build. But it's that silly rich apps phrase that's the problem. Users have way more comprehensive expectations than they did even five years ago, and the JS community does a good job at building tools and tech that tackle the problems of making heavy, complicated UI and frontend work.
Obviously there's a lot of things happening here, so just saying "JavaScript isn't terrible" might encompass a huge amount of libraries and frameworks. But if you're like me, yeah, give things another shot- I'm somehow not hating on JavaScript anymore and... gulp... I kinda love it.
How Uber developed the open source, end-to-end distributed tracing Jaeger , now a CNCF project:
Distributed tracing is quickly becoming a must-have component in the tools that organizations use to monitor their complex, microservice-based architectures. At Uber, our open source distributed tracing system Jaeger saw large-scale internal adoption throughout 2016, integrated into hundreds of microservices and now recording thousands of traces every second.
Here is the story of how we got here, from investigating off-the-shelf solutions like Zipkin, to why we switched from pull to push architecture, and how distributed tracing will continue to evolve:
https://eng.uber.com/distributed-tracing/
(GitHub Pages : https://www.jaegertracing.io/, GitHub: https://github.com/jaegertracing/jaeger)
Bindings/Operator: Python Java Node.js Go C++ Kubernetes JavaScript OpenShift C# Apache Spark