Software Alternatives, Accelerators & Startups

Quantopian VS DataMelt

Compare Quantopian VS DataMelt and see what are their differences

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Quantopian logo Quantopian

Your algorithmic investing platform

DataMelt logo DataMelt

DataMelt (DMelt), a free mathematics and data-analysis software for scientists, engineers and students.
  • Quantopian Landing page
    Landing page //
    2023-07-27
  • 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

Quantopian

$ Details
-
Platforms
-
Release Date
-

DataMelt

$ Details
freemium
Platforms
Linux Windows Mac OSX Java Cross Platform
Release Date
2020 June

Quantopian features and specs

  • Community Collaboration
    Quantopian provided a platform for users to share and collaborate on trading algorithms, enabling users to learn from each other and improve their strategies.
  • Access to Data
    Quantopian offered access to a wide range of financial data sets, which allowed users to develop and back-test their algorithms using historical data.
  • Comprehensive Development Environment
    It featured an integrated development environment (IDE) with tools for coding, testing, and back-testing trading strategies in Python, which was user-friendly and powerful.
  • Educational Resources
    Quantopian provided various educational resources, including lectures, tutorials, and a supportive community forum, which were beneficial for both beginners and experienced traders.
  • Competition and Incentives
    Quantopian organized contests that incentivized users to develop successful trading algorithms, with the potential to receive a live trading allocation from the company.

Possible disadvantages of Quantopian

  • Shutting Down Services
    Quantopian shut down its retail offering in 2020, which meant that users could no longer use their platform for developing and testing new algorithms.
  • Limited Live Trading Options
    Users found limited options for deploying their strategies into live trading. Quantopian allowed this only for algorithms selected for allocation, which reduced accessibility for many users.
  • Dependence on Platform
    Users who developed algorithms on Quantopian's platform were heavily dependent on it, and when it shut down, they had to transition to other platforms, which could be challenging.
  • Resource Limitations
    There were computational and resource limitations for users, which could restrict the complexity of the algorithms and back-testing users could perform without additional infrastructure.
  • Portfolio Selection Process
    The selection process for having algorithms licenced for live trading allocation was competitive and not transparent to many users, which could lead to frustration.

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.

Quantopian videos

Algorithmic Trading with Python and Quantopian p. 1

More videos:

  • Review - Quantopian, simple strategies

DataMelt videos

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

Add video

Category Popularity

0-100% (relative to Quantopian and DataMelt)
Finance
100 100%
0% 0
Technical Computing
0 0%
100% 100
Development
100 100%
0% 0
Office & Productivity
0 0%
100% 100

Questions & Answers

As answered by people managing Quantopian 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

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Reviews

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

Quantopian Reviews

We have no reviews of Quantopian yet.
Be the first one to post

DataMelt Reviews

  1. Great 3D graphics

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

What are some alternatives?

When comparing Quantopian 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.

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

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.