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Backtrader VS DataMelt

Compare Backtrader VS DataMelt and see what are their differences

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Backtrader logo Backtrader

Backtrader is a complete and advanced python framework that is used for backtesting and trading.

DataMelt logo DataMelt

DataMelt (DMelt), a free mathematics and data-analysis software for scientists, engineers and students.
  • Backtrader Landing page
    Landing page //
    2021-09-30
  • DataMelt Landing page
    Landing page //
    2019-07-18

DataMelt is a Java program for statistics, general data analysis and data visualization. The program is often termed "computational platform" since it can be used with different programming languages (Java, Python, Groovy..). DataMelt is not limited to a single programming language. The program is used for numeric computation, statistics, analysis of large data volumes ("big data") and scientific visualization. Full description: https://handwiki.org/wiki/Software:DataMelt

Backtrader

Website
backtrader.com
$ Details
Platforms
-
Release Date
-
Edit details

DataMelt

Website
datamelt.org
$ Details
freemium
Platforms
Linux Windows Mac OSX Java Cross Platform
Release Date
2020 June
Edit details

Backtrader features and specs

  • Versatility
    Backtrader supports a wide variety of data sources and formats, as well as different types of financial instruments, allowing for extensive backtesting and live trading capabilities.
  • Community and Documentation
    The platform has a strong community and comprehensive documentation, making it easier for new users to get started and for experienced users to troubleshoot and optimize their strategies.
  • Python Integration
    Written in Python, Backtrader allows users to leverage Python's extensive ecosystem of libraries for data analysis, machine learning, and other financial computations.
  • Open Source
    As an open-source project, users can modify and extend the platform to meet their specific trading and testing needs without restrictions, and contribute to its development.
  • Flexibility in Strategy Design
    Backtrader offers a flexible and intuitive framework to design complex trading strategies, enabling users to test multiple strategies with different parameters efficiently.

Possible disadvantages of Backtrader

  • Steep Learning Curve
    Despite its flexibility, new users may find Backtrader's extensive features and options overwhelming, requiring a significant amount of time to learn and effectively utilize.
  • Performance Issues
    For very large datasets, Backtrader might experience performance bottlenecks or require additional optimization, as Python is not the fastest language for high-frequency backtesting.
  • Limited Technical Support
    As a community-driven open-source project, Backtrader might lack the formal technical support and customer service that comes with commercial trading platforms.
  • Complexity in Live Trading
    Transitioning from backtesting to live trading can require significant additional setup and potential custom development, especially in integrating broker APIs.
  • Outdated Resources
    Some educational materials and tutorials may be outdated, leading to confusion due to interface or feature updates that are not well-documented.

DataMelt features and specs

  • Versatility
    DataMelt supports a wide range of programming languages including Java, Jython, Groovy, and JRuby, making it versatile for users familiar with different coding environments.
  • Rich Libraries
    It offers a comprehensive set of scientific libraries for numerical computation, data analysis, and visualization, which can be beneficial for complex scientific research and data processing tasks.
  • Cross-Platform
    DataMelt is platform-independent, running on any operating system that supports Java, such as Windows, macOS, and Linux. This makes it accessible to a wide audience.
  • Integrated Development Environment
    DataMelt provides a powerful IDE that integrates coding, plotting, and visualization tools, streamlining the workflow for developers and researchers.
  • Free and Open Source
    The core functionality of DataMelt is available for free, which can be appealing to individuals and organizations looking for budget-friendly computational tools.

Backtrader videos

+ Add

Backtrader Python Review

More videos:

  • Review - Algorithmic Trading with Python and Backtrader (Part 1)
  • Review - Backtrader Live Forex Trading with Interactive Brokers (Part 1)

DataMelt videos

No DataMelt videos yet. You could help us improve this page by suggesting one.

Add video

Category Popularity

0-100% (relative to Backtrader and DataMelt)

Backtrader

DataMelt

Finance
100 100%
Finance
0% 0
Technical Computing
0 0%
Technical Computing
100% 100
Development
100 100%
Development
0% 0
Office & Productivity
0 0%
Office & Productivity
100% 100

Questions & Answers

As answered by people managing Backtrader and DataMelt.

How would you describe the primary audience of your product?

DataMelt's answer:

students and data scientists

What's the story behind your product?

DataMelt's answer:

DataMelt has its roots in particle physics where data mining is a primary task. It was created as Software:jHepWork project in 2005 and it was initially written for data analysis for particle physics.

What makes your product unique?

DataMelt's answer:

Multiplatform. Supports multiple programming languages: Java, Python (Jython), Groovy, Ruby

Why should a person choose your product over its competitors?

DataMelt's answer:

Large database of examples and code snippets https://datamelt.org/code/

Who are some of the biggest customers of your product?

DataMelt's answer:

Students at universities and data scientists.

Which are the primary technologies used for building your product?

DataMelt's answer:

Java (JDK any new new release including JDK20)

User comments

Share your experience with using Backtrader and DataMelt. For example, how are they different and which one is better?
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Reviews

These are some of the external sources and on-site user reviews we've used to compare Backtrader and DataMelt

Backtrader Reviews

We have no reviews of Backtrader yet.
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DataMelt Reviews

  1. J.Mayear
    Great 3D graphics

    I like this DataMelt analysis program since it has many 2D/3D visualisation and a massive number of practical examples

Social recommendations and mentions

Based on our record, Backtrader seems to be more popular. It has been mentiond 3 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Backtrader mentions (3)

  • My reality of trading and how i wish i had never started.
    I do like what I see and hear about backtrader.com. I would say they are a notable exception to my general rule of not trusting or using backtesting frameworks. However, I still think it is important to understand how the framework you are using works. So if you are using backtrader for backtesting you still need to put in the time to understand the backtesting engine. Source: over 3 years ago
  • My reality of trading and how i wish i had never started.
    What about backtrader.com? And I feel like it would be step 2 after you at least have something to backtrade and test haha. Source: over 3 years ago
  • I need to know what can go wrong with my 'masterplan'
    Backtesting is basically applying your strategy on historical price data to see if it makes money. I've used Backtrader it works decently well: https://backtrader.com/. Source: almost 5 years ago

DataMelt mentions (0)

We have not tracked any mentions of DataMelt yet. Tracking of DataMelt recommendations started around Mar 2021.

What are some alternatives?

When comparing Backtrader and DataMelt, you can also consider the following products

QuantConnect - QuantConnect provides a free algorithm backtesting tool and financial data so engineers can design algorithmic trading strategies. We are democratizing algorithm trading technology to empower investors.

LabPlot - LabPlot is a KDE-application for interactive graphing and analysis of scientific data.

Quantopian - Your algorithmic investing platform

SciDaVis - SciDAVis is a free application for Scientific Data Analysis and Visualization.

CloudQuant - Crowd based algorithmic trading development and backtesing for stock market trading.

RJS Graph - RJS Graph is an artificial intelligence-based data management platform that allows users or developers to organize the data by manipulating the binaries, scientific, mathematical, and other insights with accurate results.

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