Software Alternatives, Accelerators & Startups

Artifactory VS Plotly

Compare Artifactory VS Plotly and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Artifactory logo Artifactory

The worldโ€™s most advanced repository manager.

Plotly logo Plotly

Low-Code Data Apps
  • Artifactory Landing page
    Landing page //
    2023-10-02
  • Plotly Landing page
    Landing page //
    2023-07-31

Artifactory features and specs

  • Universal Repository Manager
    Artifactory supports a wide range of packaging formats, including Maven, Gradle, Docker, npm, and more. This makes it extremely versatile for organizations using multiple types of build artifacts.
  • Integration with CI/CD Tools
    Artifactory integrates seamlessly with a variety of continuous integration and continuous deployment tools like Jenkins, CircleCI, and GitLab, which helps streamline the build and release process.
  • Security and Access Control
    It provides robust security features including fine-grained access control, LDAP integration, and advanced auditing capabilities to ensure that only authorized personnel can access specific artifacts.
  • High Availability
    Artifactory offers high availability setups, enabling it to be configured in a redundant and load-balanced setup to ensure maximum uptime and reliability.
  • Efficient Storage Management
    It provides advanced storage management capabilities, such as artifact de-duplication, and optimization features to better manage storage resources.
  • Performance and Scalability
    Artifactory is designed to handle large-scale deployments and provides caching mechanisms to significantly improve performance and reduce build times.
  • Enterprise-Grade Features
    Artifactory comes with enterprise-grade features such as disaster recovery, multi-push replication, and advanced metrics, which are particularly useful for large organizations.

Possible disadvantages of Artifactory

  • Cost
    Artifactory can be expensive, especially for smaller organizations or individual developers, due to its licensing fees for enterprise features.
  • Complexity
    Setting up and managing Artifactory can be complex, requiring specialized knowledge and potentially a dedicated team to handle its configuration and maintenance.
  • Resource Intensive
    Artifactory can be resource-intensive, particularly in larger setups. It may require significant memory, CPU, and storage resources to run efficiently.
  • Learning Curve
    There can be a steep learning curve for new users to fully understand and utilize all of Artifactory's features and best practices in managing artifact repositories.
  • User Interface
    Some users find the user interface to be less intuitive compared to other repository management solutions, which can slow down the adoption process.
  • Overhead
    The system could add operational overhead in terms of maintenance, updates, and troubleshooting, which may require additional time and resources.

Plotly features and specs

  • Interactivity
    Plotly offers highly interactive plots that allow users to pan, zoom, and hover over data points for more information. This enhances the user experience and provides deeper insights.
  • High-quality visualizations
    It provides aesthetically pleasing and highly customizable charts, making it suitable for publication-quality visuals.
  • Versatility
    Plotly supports multiple chart types including line charts, scatter plots, bar charts, and 3D plots, making it suitable for a wide range of applications.
  • Python integration
    Plotly is well-integrated with Python and works seamlessly with other popular data science libraries like Pandas, NumPy, and Scikit-learn.
  • Web-based
    The plots can be easily embedded in web applications or dashboards, making it ideal for sharing insights over the internet.
  • Open-source
    Plotly offers an open-source version, which allows users to create and share visualizations without any cost.

Possible disadvantages of Plotly

  • Performance
    Rendering very large datasets can sometimes be slow, which may not be suitable for real-time data visualization requirements.
  • Learning curve
    Even though the library is well-documented, the extensive range of features can have a steep learning curve for beginners.
  • Cost for advanced features
    While the basic functionality is free, more advanced features, such as export to certain formats and additional customizable options, require a paid subscription.
  • Dependency management
    Plotly has a number of dependencies that need to be managed properly, which can sometimes complicate the setup process.
  • Complexity
    For simple visualizations, Plotly might be overkill and simpler libraries like Matplotlib or Seaborn could be more appropriate.

Analysis of Artifactory

Overall verdict

  • Yes, Artifactory by JFrog is generally considered a good choice for managing and automating binary storage and distribution across different software development and deployment processes.

Why this product is good

  • Artifactory is highly regarded due to its universal repository capabilities, supporting all major packaging formats including Maven, npm, NuGet, and Docker. It integrates seamlessly with CI/CD tools, provides high availability, supports multi-site replication, and has advanced security features for artifact management. Its ability to handle large-scale deployments efficiently makes it suitable for enterprises.

Recommended for

  • Organizations that require a reliable and scalable solution for binary repository management.
  • Teams that are using a wide variety of technology stacks and want a single repository solution.
  • DevOps teams that prioritize automation and want integration with their CI/CD pipelines.
  • Companies looking for enterprise-grade security and compliance features in their artifact lifecycle management.

Analysis of Plotly

Overall verdict

  • Overall, Plotly is a strong choice for those looking to create dynamic and interactive data visualizations, thanks to its range of features and ease of integration with web technologies.

Why this product is good

  • Plotly is considered good because it offers a comprehensive suite of tools for creating interactive visualizations that can be used in web applications, reports, and dashboards. It supports many different types of plots, is easy to use for both beginners and experienced developers, and integrates well with popular programming languages like Python, R, and JavaScript.

Recommended for

    Plotly is recommended for data scientists, analysts, and developers who need to create interactive and visually appealing data visualizations. It's particularly useful for those who work with Python or R and want the ability to embed their visualizations in web applications or dashboards.

Artifactory videos

Introduction to Artifactory

More videos:

  • Review - [Webinar] Introducing JFrog Mission Control
  • Review - [Webinar] Introduction to Artifactory
  • Review - JFrog Mission Control - Accelerate Software Delivery at Global Scale
  • Review - [Webinar] Introduction to Artifactory

Plotly videos

Create Real-time Chart with Javascript | Plotly.js Tutorial

More videos:

  • Review - Introducing plotly.py 3.0
  • Review - Is Plotly The Better Matplotlib?
  • Tutorial - Plotly Tutorial 2021
  • Review - Data Visualization as The First and Last Mile of Data Science Plotly Express and Dash | SciPy 2021

Category Popularity

0-100% (relative to Artifactory and Plotly)
Git
100 100%
0% 0
Data Visualization
0 0%
100% 100
Code Collaboration
100 100%
0% 0
Charting Libraries
0 0%
100% 100

User comments

Share your experience with using Artifactory and Plotly. For example, how are they different and which one is better?
Log in or Post with

Reviews

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

Artifactory Reviews

Repository Management Tools
Artifactory is the enterprise-ready repository manager available today, supporting secure, clustered, High Availability Docker registries. JFrog is a universal artifact repository and distribution platform. A unique DevOps tool, JFrog Artifactory is a universal artifact repository manager that fully supports software packages created by any language or technology. Integrates...
Source: mindmajix.com
Choosing a Binary Repository Manager
JFrog bills Artifactory as the first universal binary repository manager and supports a wide range of package managers, including Maven, npm, Go Registry, NuGet, PyPI, RubyGems, Conan, RPM, Debian, and Helm. Itโ€™s been around since before 2009. A complete list of supported package managers can be found here.
What is Artifactory?
Artifactory is a branded term to refer to a repository manager that organizes all of your binary resources. These resources can include remote artifacts, proprietary libraries, and other third-party resources. A repository manager pulls all of these resources into a single location. The word โ€œArtifactoryโ€ refers to the JFrog product, the JFrog Artifactory, but there are...

Plotly Reviews

Best 8 Redash Alternatives in 2023 [In Depth Guide]
Plotly is specifically designed for companies who want to build and deploy analytic applications like dashboards using Python, Julia, or R without needing DevOps or Javascript developers.
Source: www.datapad.io
5 Best Python Libraries For Data Visualization in 2023
Plotly is a web-based data visualization toolkit that comes with unique functionalities such as dendrograms, 3D charts, and also contour plots, which is not very common in other libraries. It has a great API offering scatter plots, line charts, bar charts, error bars, box plots, and other visualizations. Plotly can even be accessed from a Python Notebook.
Top 8 Python Libraries for Data Visualization
Plotly is a free open-source graphing library that can be used to form data visualizations. Plotly (plotly.py) is built on top of the Plotly JavaScript library (plotly.js) and can be used to create web-based data visualizations that can be displayed in Jupyter notebooks or web applications using Dash or saved as individual HTML files. Plotly provides more than 40 unique...
5 top picks for JavaScript chart libraries
Plotly is a graphing library thatโ€™s available for various runtime environments, including the browser. It supports many kinds of charts and graphs that we can configure with a variety of options.

Social recommendations and mentions

Plotly might be a bit more popular than Artifactory. We know about 34 links to it since March 2021 and only 25 links to Artifactory. 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.

Artifactory mentions (25)

  • Continuous integration with containers and inceptions
    Note1: For container storage you can use any registry available in applications like Artifactory but you can also use cloud services like AWS's ECR, AZURE's Container Registry or GCP's Container Registry. - Source: dev.to / 8 months ago
  • Docker limits unauthenticated pulls to 10/HR/IP from Docker Hub, from March 1
    Does anyone recommend some pull-through registry to use? Docker Docs has some recommendations [0], but I wonder how feature complete it is. I'd like to find something that: - Can pull and serve private images - Has UI to show a list of downloaded images, and some statistics on how much storage and bandwidth they use - Can run periodic GC to delete unused images - (maybe) Can be set up to pre-download new tags IIRC... - Source: Hacker News / over 1 year ago
  • Ask HN: Is NPM Having an Outage?
    This site is hilariously fucked on mobile https://jfrog.com/artifactory. - Source: Hacker News / over 1 year ago
  • How to Create an NPM Packages using Rollup.js + Lerna.js + Jfrog Artifactory
    JFrog Artifactory is a universal artifact repository manager that enables organizations to store, manage, and distribute software packages and artifacts across the entire development lifecycle. It supports a wide range of package formats, including Docker, Maven, npm, PyPI, and more, making it a versatile solution for DevOps and CI/CD pipelines. - Source: dev.to / over 1 year ago
  • Efficient Kubernetes Cluster Deployment: Accelerating Setup with EKS Blueprints
    For advanced customization requirements, EKS Blueprints offers flexibility by allowing easy overrides of default Helm values. For instance, you can effortlessly replace Docker images specified in the values.yaml file with private Docker repositories like ECR or Artifactory. - Source: dev.to / over 1 year ago
View more

Plotly mentions (34)

  • How to Analyze 47 Million Hacker News Posts: A Data Scientist's Dream Dataset Just Got Better
    Let's dive into some practical examples. First, you'll need to set up your environment with the right tools. I recommend using pandas for data manipulation and plotly for visualization. - Source: dev.to / 4 months ago
  • Python for Data Visualization: Best Tools and Practices
    Plotly is perfect for interactive visualizations. You can create interactive charts and graphs that allow users to hover, click, and zoom in. Plotly is also great for web-based visuals, making it easy to share your findings online. - Source: dev.to / over 1 year ago
  • Generative AI Powered QnA & Visualization Chatbot
    Front End: A React application that leverages React-Chatbotify library to easily integrate a chatbot GUI. It also uses the Plotly library to display the charts/visualizations. The generative AI implementation and details are entirely abstracted from the front end. The front-end application depends on a single REST endpoint of the backend application. - Source: dev.to / over 1 year ago
  • Build a Stock Dashboard in less than 40 lines of Python code!๐Ÿค“
    In this tutorial, Mariya Sha will guide you through building a stock value dashboard using Taipy, Plotly, and a dataset from Kaggle. - Source: dev.to / over 1 year ago
  • Essential Deep Learning Checklist: Best Practices Unveiled
    How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / about 2 years ago
View more

What are some alternatives?

When comparing Artifactory and Plotly, you can also consider the following products

Git - Git is a free and open source version control system designed to handle everything from small to very large projects with speed and efficiency. It is easy to learn and lightweight with lighting fast performance that outclasses competitors.

D3.js - D3.js is a JavaScript library for manipulating documents based on data. D3 helps you bring data to life using HTML, SVG, and CSS.

Atlassian Bitbucket Server - Atlassian Bitbucket Server is a scalable collaborative Git solution.

RAWGraphs - RAWGraphs is an open source app built with the goal of making the visualization of complex data...

GitKraken - The intuitive, fast, and beautiful cross-platform Git client.

Tableau - Tableau can help anyone see and understand their data. Connect to almost any database, drag and drop to create visualizations, and share with a click.