Software Alternatives, Accelerators & Startups

Plotly VS Datagaps

Compare Plotly VS Datagaps and see what are their differences

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Plotly logo Plotly

Low-Code Data Apps

Datagaps logo Datagaps

Gartner-listed DataOps + Data Observability platform. One unified suite to validate ETL, BI, Data Quality, and AI pipelines. 100+ enterprises.
  • Plotly Landing page
    Landing page //
    2023-07-31
  • Datagaps DataGaps DataOps Suite Dashboard
    DataGaps DataOps Suite Dashboard //
    2026-07-28

Datagaps makes data trustworthy โ€” for confident BI analytics, compliant AI models, zero-defect data migrations and data transformations at scale.

The only platform recognized by Gartner in BOTH the DataOps Tools AND Data Observability market guides, Datagaps unifies what enterprises have historically stitched together from three or more tools: ETL testing, BI validation, data quality monitoring, and test data management โ€” in a single platform with shared rules, lineage, and governance.

Powered by Agentic AI, the DataOps Suite auto-generates tests, self-heals with schema changes, summarizes BI report differences, and recommends smart quality rules โ€” so data teams spend time on decisions, not defect hunting. Outcomes delivered to 100+ enterprise customers: 500B+ Records validated across ETL & cloud pipelines 10M+ Automated test cases run with zero manual scripting 80% Faster test cycles vs. manual testing approach 60% Reduction in data errors detected before production 70% Reduction in ETL validation spend 200+ Native data source connectors

SOC 2 Type II certified. US Patented ELV architecture. Informatica Certified. Embedded LLM โ€” your data never leaves your environment.

Products: DataOps Suite | ETL Validator | BI Validator | Data Quality Monitor | Test Data Manager

Platforms: 200+ Integration flexibility such as Snowflake, Databricks, Azure Synapse, AWS Redshift, Power BI, Tableau, Oracle Analytics, Salesforce, Informatica, dbt

Datagaps

Pricing URL
-
Release Date
2010 July
Startup details
Country
United States
State
virginia
City
herndon
Founder(s)
Narendar Yalamanchilli
Employees
100 - 249

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.

Datagaps features and specs

No features have been listed yet.

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 Datagaps

Overall verdict

  • Datagaps is a solid choice for organizations seeking specialized data testing and quality automation tools, particularly for ETL, BI, and data warehouse validation. It offers a comprehensive suite tailored to data-centric QA needs, though it may be less known than larger enterprise testing platforms.

Why this product is good

  • Offers a dedicated suite for ETL, data warehouse, and BI testing automation (DataOps Suite)
  • Supports test automation for reports, dashboards, and data migration validation
  • Provides no-code/low-code test creation, making it accessible to non-technical testers
  • Includes robust data reconciliation and comparison features across multiple data sources
  • Integrates with popular BI tools like Tableau, Power BI, and various databases and cloud platforms
  • Helps reduce manual testing effort and time for large-scale data validation projects

Recommended for

  • Enterprises with complex ETL and data warehouse testing needs
  • QA teams responsible for validating BI reports and dashboards
  • Organizations undergoing data migration or cloud data platform transitions
  • Companies seeking to automate data quality and reconciliation checks
  • Teams looking for no-code testing solutions for data pipelines
  • Businesses needing regulatory or compliance-driven data validation

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

Datagaps videos

Datagaps DataOps Suite: The Comprehensive End-to-End Data Validation Platform

Category Popularity

0-100% (relative to Plotly and Datagaps)
Data Visualization
100 100%
0% 0
Data Quality
0 0%
100% 100
Charting Libraries
100 100%
0% 0
Testing
0 0%
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 Plotly and Datagaps

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.

Datagaps Reviews

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

Social recommendations and mentions

Based on our record, Plotly seems to be more popular. It has been mentiond 34 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.

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

Datagaps mentions (0)

We have not tracked any mentions of Datagaps yet. Tracking of Datagaps recommendations started around Sep 2022.

What are some alternatives?

When comparing Plotly and Datagaps, 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.

iCEDQ - iceDQ provides the ability to test your data warehouse, data migration, big data and monitor the data for compliance.

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

RightData - Automated ETL test validation

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.

Google Charts - Interactive charts for browsers and mobile devices.