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Steampipe VS Plotly

Compare Steampipe VS Plotly and see what are their differences

Modelence
Create production-ready applications with zero code sponsored
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Contents:
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  3. » Reviews
  4. » Alternatives

Steampipe logo Steampipe

Steampipe: select * from cloud; The extensible SQL interface to your favorite cloud APIs select * from AWS, Azure, GCP, Github, Slack etc.

Plotly logo Plotly

Low-Code Data Apps
  • Steampipe Landing page
    Landing page //
    2023-09-30
  • Plotly Landing page
    Landing page //
    2023-07-31

Steampipe features and specs

  • Unified Interface
    Steampipe provides a unified SQL-based interface to query data from various cloud services and APIs, simplifying data access.
  • Open Source
    Being open source, Steampipe allows for community contributions, transparency, and flexibility in adapting the tool to specific needs.
  • Plugin Ecosystem
    Steampipe has a growing ecosystem of plugins that enable easy integration with numerous services, enhancing its versatility.
  • Real-Time Data Access
    It facilitates real-time querying of data from live APIs, which is beneficial for up-to-date insights and monitoring.
  • Cross-Platform Compatibility
    Steampipe is designed to work on multiple platforms, including Windows, MacOS, and Linux, making it accessible to a wide range of users.

Possible disadvantages of Steampipe

  • Complex Setup
    Initial setup and configuration can be complex, requiring a good understanding of SQL and the specific APIs being used.
  • Performance Overhead
    Query performance may be impacted due to the abstraction layer and real-time consolidation of data from multiple sources.
  • Limited Community Support
    As a relatively new tool, Steampipe may have limited community support and fewer resources compared to more established alternatives.
  • Resource Intensive
    Running multiple queries against APIs and cloud services can become resource intensive, potentially increasing costs and load on systems.
  • Learning Curve
    Users unfamiliar with SQL may face a learning curve in effectively utilizing Steampipe for querying different data sources.

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 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.

Steampipe videos

+ Add

Superbooth 2023: Erica Synths - Steampipe

More videos:

  • Review - BEST SYNTHS @ SUPERBOOTH23: PWM Mantis, UDO Super Gemini, Erica Synths STEAMPIPE… and more
  • Review - Erica Synths STEAMPIPE The Synth with no oscillators!

Plotly videos

+ Add

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 Steampipe and Plotly)

Steampipe

Plotly

Big Data
100 100%
Big Data
0% 0
Data Visualization
0 0%
Data Visualization
100% 100
Cloud Infrastructure
100 100%
Cloud Infrastructure
0% 0
Charting Libraries
0 0%
Charting Libraries
100% 100

User comments

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Reviews

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

Steampipe Reviews

We have no reviews of Steampipe yet.
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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.
Source: www.technotification.com
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...
Source: www.geeksforgeeks.org
5 top picks for JavaScript chart libraries
Plotly is a graphing library that’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.
Source: blog.logrocket.com

Social recommendations and mentions

Steampipe might be a bit more popular than Plotly. We know about 43 links to it since March 2021 and only 34 links to Plotly. 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.

Steampipe mentions (43)

  • Executable Is a SQLite Database
    Check out https://steampipe.io/, available as sqlite/postgtesql extensions. - Source: Hacker News / 12 days ago
  • Build API integrations with SQL and YAML – no SaaS lock-in, no drag-and-drop UIs
    The request / data fetching is interesting in how "easy" it is to write. I did basic perusal of the examples, but I'd be interested to see what it looks like with rate-limited endpoints and concurrent requests. Another tangentially related project is https://steampipe.io/ though it is for exposing APIs via Postgres tables and the clients are written using Go code and shared through a marketplace. - Source: Hacker News / over 1 year ago
  • Cyphernetes: A Query Language for Kubernetes
    I really really like Steampipe to do this kind of query: https://steampipe.io, which is essentially PostgreSQL (literally) to query many different kind of APIs, which means you have access to all PostgreSQL's SQL language can offer to request data. They have a Kubernetes plugin at https://hub.steampipe.io/plugins/turbot/kubernetes and there are a couple of things I really like: * it's super easy to request... - Source: Hacker News / over 1 year ago
  • DuckDB Doesn't Need Data to Be a Database
    Https://steampipe.io/ showcases some really interesting scenarios for using FDWs in place of regular ETL and API integrations. - Source: Hacker News / over 2 years ago
  • Cloud Tools You Probably Haven't Heard Of
    Steampipe is a tool for querying cloud APIs and other data sources using SQL in a zero-ETL manner. - Source: dev.to / over 2 years 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 / 6 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!🤓
    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 / almost 2 years 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 Steampipe and Plotly, you can also consider the following products

CloudQuery - CloudQuery enables you to assess, audit, and evaluate the configurations of your cloud assets.

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.

StackQL.io - Query, provision, secure & operate cloud resources using SQL

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

Turbot - Turbot's guardrails deliver automated operational, cloud security and cloud compliance controls of AWS deployments and other cloud enterprise infrastructure. Learn more.

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.

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