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Plotly VS InfluxData

Compare Plotly VS InfluxData and see what are their differences

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Plotly logo Plotly

Low-Code Data Apps

InfluxData logo InfluxData

Scalable datastore for metrics, events, and real-time analytics.
  • Plotly Landing page
    Landing page //
    2023-07-31
  • InfluxData Landing page
    Landing page //
    2023-07-30

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.

InfluxData features and specs

  • High Performance
    InfluxData's InfluxDB is designed to handle high write and query loads, making it suitable for time-series data and real-time applications.
  • Open-Source
    The core InfluxDB product is open-source, allowing for transparency, community contributions, and the option to self-host the database.
  • Scalability
    InfluxDB offers horizontal scalability, enabling users to handle increasing volumes of data efficiently through clustering.
  • Built-In Data Processing
    InfluxData offers integrated tools for data processing and scripting, such as Kapacitor for real-time processing and Flux for advanced querying.
  • Rich Ecosystem
    InfluxData provides a comprehensive ecosystem including Telegraf for data collection, Chronograf for visualization, and Kapacitor for alerting and processing.
  • Time-Series Focused
    InfluxDB is optimized for time-series data, offering specialized features like time-based retention policies, continuous queries, and downsampling.
  • Easy Integration
    InfluxDB integrates well with many third-party data visualization and monitoring tools such as Grafana, making it easier to build end-to-end solutions.

Possible disadvantages of InfluxData

  • Complexity
    The comprehensive features and tools in the InfluxData ecosystem can result in a steeper learning curve, especially for novices.
  • Cost
    While the open-source version is free, the enterprise and cloud-hosted versions come with a cost, which can be significant for small to mid-sized businesses.
  • Resource Intensive
    InfluxDB can be resource-intensive, especially under high loads, requiring significant hardware resources for optimal performance.
  • Limited SQL Support
    InfluxDB doesn’t fully support SQL, which can be a hurdle for users accustomed to traditional relational databases. It uses its own query languages like InfluxQL and Flux.
  • Fragmented Documentation
    Some users find the documentation fragmented or lacking in depth, which can make troubleshooting and advanced usage more challenging.
  • Data Backup and Restore
    Managing backups and restores in InfluxDB can be intricate and may require additional effort and tools to ensure data integrity and availability.

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.

Analysis of InfluxData

Overall verdict

  • Yes, InfluxData is considered good for dealing with time-series data.

Why this product is good

  • Specialized Time-Series Database: InfluxData offers InfluxDB, which is specifically tailored for handling time-series data, making it highly efficient for this purpose.
  • Scalability: InfluxDB is known for its high performance and scalability, which is advantageous for applications requiring the processing of large volumes of data quickly.
  • Rich Ecosystem: It provides a comprehensive suite of tools for data collection, analysis, and visualization, which includes the TICK stack (Telegraf, InfluxDB, Chronograf, and Kapacitor).
  • Ease of Use: The product offerings are designed to be user-friendly, reducing the complexity of setting up and managing time-series databases.
  • Strong Community Support: InfluxData has a robust community and good documentation, which is beneficial for troubleshooting and getting the most out of its tools.

Recommended for

  • IoT Applications: For organizations dealing with IoT devices generating large amounts of time-stamped data.
  • DevOps Monitoring: Useful for monitoring infrastructure and applications due to its ability to collect and store real-time metrics.
  • Finance: Can be employed to track stock prices, or other financial metrics over time.
  • Research: For scientific data that requires precise timestamping and quick retrieval.
  • Energy Management: Ideal for tracking and analyzing power consumption over time.

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

InfluxData videos

+ Add

Barbara Nelson [InfluxData] | Best Practices for Data Ingestion into InfluxDB

Category Popularity

0-100% (relative to Plotly and InfluxData)

Plotly

InfluxData

Data Visualization
100 100%
Data Visualization
0% 0
Databases
0 0%
Databases
100% 100
Data Dashboard
100 100%
Data Dashboard
0% 0
Time Series Database
0 0%
Time Series Database
100% 100

User comments

Share your experience with using Plotly and InfluxData. 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 Plotly and InfluxData

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

InfluxData Reviews

ReductStore vs. MinIO & InfluxDB on LTE Network: Who Really Wins the Speed Race?
Maintaining consistency between multiple databases, like MinIO and InfluxDB, adds a layer of complexity. In our setup, MinIO, used for blob storage, is linked to data points in InfluxDB via its filename. Any inconsistencies or mismatches between the two could potentially result in data loss. Furthermore, we need to query both databases, which is quite inefficient. Lastly,...
Source: www.reduct.store
Apache Druid vs. Time-Series Databases
We occasionally get questions regarding how Apache Druid differs from time-series databases (TSDB) such as InfluxDB or Prometheus, and when to use each technology. This short post serves to help answer these questions.
Source: imply.io
4 Best Time Series Databases To Watch in 2019
InfluxDB is part of the TICK stack : Telegraf, InfluxDB, Chronograf and Kapacitor. InfluxData provides, out of the box, a visualization tool (that can be compared to Grafana), a data processing engine that binds directly with InfluxDB, and a set of more than 50+ agents that can collect real-time metrics for a lot of different data sources.
Source: medium.com

Social recommendations and mentions

Based on our record, Plotly seems to be a lot more popular than InfluxData. While we know about 33 links to Plotly, we've tracked only 2 mentions of InfluxData. 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.

Plotly mentions (33)

  • 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 / 3 months 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 / 5 months 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 / 6 months 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 1 year ago
  • Python equivalent to power bi/power query?
    For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: over 1 year ago
View more

InfluxData mentions (2)

  • Can i log data into excel/csv using aws?
    I would highly recommend using a proper Time Series Database like QuestDB or InfluxDB to do this instead. You can always export data from wither of those two into Excel if your boss wants it in excel, but it's much easier to do data transformations, create graphs and reports, etc. If you have all the data in a proper database. Source: over 3 years ago
  • How to stream IoT data into Excel
    I would suggest using something better suited to IoT data than ... a spreadsheet. I'd recommend looking at one of the Time Series Databases for this. 1) QuestDB or 2) InfluxDB as these are much better suited to streaming data. Source: over 3 years ago

What are some alternatives?

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

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.

TimescaleDB - TimescaleDB is a time-series SQL database providing fast analytics, scalability, with automated data management on a proven storage engine.

Chart.js - Easy, object oriented client side graphs for designers and developers.

Prometheus - An open-source systems monitoring and alerting toolkit.

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

Amazon EMR - Amazon Elastic MapReduce is a web service that makes it easy to quickly process vast amounts of data.

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