Software Alternatives, Accelerators & Startups

GNU Make VS Datapane

Compare GNU Make VS Datapane and see what are their differences

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GNU Make logo GNU Make

GNU Make is a tool which controls the generation of executables and other non-source files of a program from the program's source files.

Datapane logo Datapane

Datapane is an API-first platform for building reporting and BI tools using Python.
  • GNU Make Landing page
    Landing page //
    2023-03-12
  • Datapane Landing page
    Landing page //
    2023-09-10

GNU Make features and specs

  • Portability
    GNU Make is highly portable and can be used across various Unix-like operating systems as well as on Windows.
  • Dependency Management
    It efficiently handles complex dependencies between various parts of the software, ensuring that changes are propagated properly.
  • Open Source
    Being open-source software, GNU Make is freely available and can be modified according to user needs.
  • Wide Adoption
    It is widely adopted in the industry, which means that there is extensive documentation and a large community for support.
  • Efficiency
    GNU Make speeds up the build process by only recompiling the necessary parts of the codebase.

Possible disadvantages of GNU Make

  • Complex Syntax
    The syntax of GNU Makefiles can become very complex, especially for large projects, making them hard to read and maintain.
  • Limited Cross-Platform Scripting
    While the tool itself is cross-platform, Makefiles can sometimes include shell commands that are not portable.
  • Steep Learning Curve
    Beginners may find it challenging to grasp the concepts and syntax of GNU Make, leading to a steep learning curve.
  • Debugging Difficulty
    Debugging Makefiles can be difficult, with limited tools available to trace or step through the make process.
  • Performance Bottlenecks
    For extremely large projects, performance can become an issue, as the evaluation of dependencies might become slow.

Datapane features and specs

  • Easy Report Generation
    Datapane simplifies the process of creating and sharing interactive reports using Python, allowing users to convert Python scripts and Jupyter notebooks into dynamic reports easily.
  • Integration with Python
    Datapane integrates seamlessly with Python, which is beneficial for data scientists and analysts who already utilize Python in their data pipelines and analyses.
  • Interactive Elements
    Reports can include interactive elements such as plots, tables, and controls, providing a more engaging way to present complex data insights.
  • Deployment Options
    Datapane offers multiple deployment options, including a cloud service for easy sharing and collaboration, as well as the ability to host on-premises or on private infrastructure.
  • Privacy and Security
    Users concerned about data privacy and security can choose to deploy Datapane on their infrastructure, maintaining control over their data.

Possible disadvantages of Datapane

  • Learning Curve
    Users not familiar with Python or scripting may find it challenging to get started with Datapane, as it requires coding knowledge for report creation.
  • Limited to Python
    Organizations not using Python heavily in their workflows may find Datapane less adaptable, as it primarily targets Python users.
  • Cost Considerations
    Depending on the chosen deployment and scale, there might be cost implications, particularly for the cloud-hosted version of Datapane.
  • Feature Limitations
    Some advanced customization or feature requirements might exceed the capabilities of Datapane, necessitating the use of additional tools or services.

Analysis of GNU Make

Overall verdict

  • Yes, GNU Make is a robust and reliable tool for managing build processes. Its long-established reputation and widespread use in both open-source and commercial projects underline its effectiveness and flexibility.

Why this product is good

  • GNU Make is widely used because it automates the build process, efficiently handling dependencies and detecting minimal sets of changes in source files. It is highly customizable, supports non-recursive builds, and integrates well into various development environments.

Recommended for

  • Software developers working on C/C++ projects
  • Teams looking to automate build processes
  • Projects that require cross-platform build capabilities
  • Developers who prefer command-line tools
  • Open-source project maintainers

GNU Make videos

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Datapane videos

Datapane Quick Overview

Category Popularity

0-100% (relative to GNU Make and Datapane)
JS Build Tools
100 100%
0% 0
Business Intelligence
0 0%
100% 100
Front End Package Manager
Developer Tools
0 0%
100% 100

User comments

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Social recommendations and mentions

Based on our record, Datapane seems to be more popular. It has been mentiond 8 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.

GNU Make mentions (0)

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

Datapane mentions (8)

  • How do you guys share R/Python based analyses to business stakeholders?
    PowerPoint will do. If there isn't too much data I will sometimes make a quick datapane html dashboard that I can also send their way. They like that, the plotly plots can be interactive so they can poke around. Nice quick solution that's easy to share. Source: almost 4 years ago
  • how do i convince data scientists to actually use my power bi dashboards?
    If you're going that route, check out Datapane - it's an open-source Python framework we're working on to create interactive reports from Plotly, Pandas, etc. Source: about 4 years ago
  • Ask HN: Who is hiring? (April 2022)
    Datapane | https://datapane.com | Remote (UK & Europe) Datapane is the frontend for the data science ecosystem. Our open-source library helps data scientists use the tools they love to create reports, dashboards, and apps for non-technical end-users. We are backed by some of the top investors in the world, and have grown to be the most popular way to create and share data science reports. We are proud to put the... - Source: Hacker News / over 4 years ago
  • Ask HN: Who is hiring? (January 2022)
    Datapane | https://datapane.com | Remote (Europe) Happy New Year! Datapane is the world's most popular way to create data science reports using Python. Our open-source framework is used by thousands of data scientists to create interactive reports, and our API-first platform serves over 50,000 people a month. We're a technical, remote team based in the UK and founded by YC alum and compsci PhDs. We're just closing... - Source: Hacker News / over 4 years ago
  • Free for dev - list of software (SaaS, PaaS, IaaS, etc.)
    Datapane - API for building interactive reports in Python and deploying Python scripts and Jupyter Notebooks as self-service tools. - Source: dev.to / about 5 years ago
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What are some alternatives?

When comparing GNU Make and Datapane, you can also consider the following products

CMake - CMake is an open-source, cross-platform family of tools designed to build, test and package software.

ReportServer - In Reporting Services, URLs are used to access the Report Server Web service and the web portal. Before you can use either application, you must configure at least one URL each for the Web service and the web portal.

SCons - SCons is an Open Source software construction tool—that is, a next-generation build tool.

Combit - Reporting tool for software developers to integrate reporting functions in desktop, web and cloud applications. Made for development environments such as .NET, C#, Delphi, C++, ASP.NET, ASP.NET MVC, .NET Core etc. Supports a variety of data sources.

SBT - SBT is a build tool for Scala, like Ant or Maven but with hieroglyphics.

JasperReports - JasperReports Server is a stand-alone and embeddable reporting server.