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CrashPlan VS Matplotlib

Compare CrashPlan VS Matplotlib and see what are their differences

NinjaOne
NinjaOne (Formerly NinjaRMM) provides remote monitoring and management software that combines powerful functionality with a fast, modern UI. Easily remediate IT issues, automate common tasks, and support end-users with powerful IT management tools. featured
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Contents:
  1. ยป Base Details
  2. ยป Videos
  3. ยป Reviews
  4. ยป Alternatives

CrashPlan logo CrashPlan

Protect Your Data. Anytime. Anywhere.

Matplotlib logo Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...
  • CrashPlan Home page
    Home page //
    2025-08-20
  • CrashPlan Endpoint backup platform
    Endpoint backup platform //
    2025-08-20
  • CrashPlan Microsoft OneDrive Backup Platform
    Microsoft OneDrive Backup Platform //
    2025-08-20
  • CrashPlan Microsoft SharePoint Backup Platform
    Microsoft SharePoint Backup Platform //
    2025-08-20
  • CrashPlan Microsoft Exchange Online Backup Platform
    Microsoft Exchange Online Backup Platform //
    2025-08-20

CrashPlan provides cyber resilience and data protection through a unified platform trusted by organizations worldwide. With secure, scalable backup and recovery for servers, endpoints, Microsoft 365, and Google Workspace, CrashPlan safeguards critical data against threats such as accidental deletion, ransomware, and system failure. Built with proactive threat detection and automated governance, CrashPlan ensures continuous access and compliance. Whether you back up to our cloud, your Azure instance, a local destination, or a third-party cloud, CrashPlan restores your data and your peace of mind.

  • Matplotlib Landing page
    Landing page //
    2023-06-14

CrashPlan features and specs

  • Unlimited Storage
    CrashPlan offers unlimited cloud storage for backups, allowing users to back up as much data as needed without worrying about hitting a cap.
  • Continuous Backup
    The software provides continuous, automatic backup, ensuring that data is protected in real-time without needing manual intervention.
  • File Versioning
    CrashPlan keeps multiple versions of files, allowing users to restore any previous version in case of accidental changes or deletions.
  • Cross-Platform Support
    Available for Windows, Mac, and Linux, making it versatile and suitable for various users and environments.
  • Strong Security
    Uses AES-256 bit encryption for stored files and TLS for data transfer, ensuring a high level of security for user data.
  • Flexible Restore Options
    Offers various options for restoring files, including web-based access, making it convenient to retrieve data from anywhere.
  • Platform Integration & Ecosystem
    Backups supported for Microsoft 365 (Exchange Online, SharePoint, OneDrive, Teams) and Google Workspace, including integration with identity providers (Entra ID, Google Cloud Identity)
  • Administration & Management
    Centralized admin dashboard for monitoring, policy enforcement, SSO integration, MDM compatibility, detailed reporting, and dashboard analytics

Possible disadvantages of CrashPlan

  • Cost
    While offering valuable features, it is relatively expensive compared to some rivals, potentially putting it out of reach for budget-conscious users.
  • No Mobile App
    Lacks a dedicated mobile app, which can limit accessibility and convenience for users who need to manage backups on the go.
  • Upload Speed Limits
    Some users have reported slower upload speeds for initial backups, which can be a drawback if you need to back up large amounts of data quickly.
  • Complex Interface
    The user interface can be somewhat complex and unintuitive, which might be challenging for non-technical users.
  • Limited Customer Support
    Customer support is not available 24/7, which could be an issue for users needing immediate help outside of business hours.

Matplotlib features and specs

  • Versatility
    Matplotlib can generate a wide variety of plots, ranging from simple line plots to complex 3D plots. This versatility makes it a go-to library for many scientific and technical visualizations.
  • Customization
    It offers extensive customization options for virtually every element of a plot, including colors, labels, line styles, and more, allowing users to tailor plots to meet specific needs.
  • Integrations
    Matplotlib integrates well with other Python libraries such as NumPy, Pandas, and SciPy, making it easier to plot data directly from these sources.
  • Community and Documentation
    It has a large, active community and comprehensive documentation that includes tutorials, examples, and detailed references, which can help users solve problems and improve their plot-making skills.
  • Interactivity
    Matplotlib supports interactive plots, which can be embedded in Jupyter notebooks and GUIs, allowing for dynamic data exploration and presentation.
  • Publication-Quality
    The library is capable of producing high-quality, publication-ready graphics that meet the stringent requirements of academic journals and professional presentations.

Possible disadvantages of Matplotlib

  • Complexity
    While Matplotlib offers extensive customization, it can be complex and sometimes unintuitive for beginners, requiring a steep learning curve to master all its functionality.
  • Performance
    Rendering a large number of plots or handling very large datasets can be slow, making Matplotlib less suitable for real-time data visualization.
  • Modern Aesthetics
    Out-of-the-box plots from Matplotlib can look somewhat dated compared to those from newer plotting libraries like Seaborn or Plotly, requiring additional customization to achieve a modern look.
  • 3D Plots
    Although Matplotlib supports 3D plotting, its capabilities are relatively limited and less sophisticated compared to specialized 3D plotting libraries.
  • Size and Structure
    The package is relatively large and can be slow to import. Its extensive structure can make finding specific functions and understanding the overall architecture challenging.

Analysis of CrashPlan

Overall verdict

  • CrashPlan is generally considered a good choice for both individuals and businesses looking for strong, reliable backup solutions. It is particularly favorable for users who need unlimited storage and advanced security measures. However, its features might be more than what's necessary for casual users who need simpler or more cost-effective solutions.

Why this product is good

  • CrashPlan is often praised for its unlimited cloud storage for backups, comprehensive versioning, and reliable security features. Users appreciate its focus on data protection, making it a popular choice for businesses and individuals who need robust backup solutions. The service also offers continuous data protection, ensuring that files are backed up as changes are made.

Recommended for

  • Small to medium-sized businesses needing reliable and secure backup solutions.
  • Individuals with large amounts of data to backup who want unlimited storage.
  • Users who need comprehensive file versioning and frequent backups.
  • Anyone who prioritizes data security and continuous backup capabilities.

Analysis of Matplotlib

Overall verdict

  • Yes, Matplotlib is a good library for data visualization, particularly for users who require a versatile and powerful plotting solution in Python.

Why this product is good

  • Matplotlib is highly regarded due to its extensive customization options, versatility in creating a wide range of static, animated, and interactive plots, and its large user community and support. It integrates well with other scientific libraries in Python, making it a staple for data visualization. The library is also open-source and frequently updated, ensuring it remains a reliable choice for users.

Recommended for

  • Data scientists and analysts needing to create detailed, customized visual representations of their data.
  • Researchers and engineers looking for a comprehensive plotting library that supports scientific and engineering formats.
  • Python developers who require integration with other scientific computing libraries like NumPy and Pandas.

CrashPlan videos

+ Add

Protect the Data that Matters Most with CrashPlan

Matplotlib videos

+ Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Category Popularity

0-100% (relative to CrashPlan and Matplotlib)

CrashPlan

Matplotlib

Cloud Storage
100 100%
Cloud Storage
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Backup And Disaster Recovery
100 100%
Backup And Disaster Recovery
0% 0
Technical Computing
0 0%
Technical Computing
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 CrashPlan and Matplotlib

CrashPlan Reviews

Raising Prices is Hard
Early that morning news broke that our main competitor, Crashplan, was leaving the consumer backup space. You may be saying: Wait a minute, a main competitor is leaving the market and you have a mechanism to increase your prices in place โ€” that sounds like the perfect day to raise prices! Nope. Another one of our values, is to be fair and good. Raising prices on a day when...
Source: www.backblaze.com

Matplotlib Reviews

25 Python Frameworks to Master
Matplotlib is a widely used tool for data visualization in Python. It provides an object-oriented API for embedding plots into applications.
Source: kinsta.com
5 Best Python Libraries For Data Visualization in 2023
You can use this library for multiple purposes such as generating plots, bar charts, histograms, power spectra, stemplots, pie charts, and more. The best thing about Matplotlib is you just have to write a few lines of code and it handles the rest by itself. Metaplotilib focuses on static images for publication along with interactive figures using toolkits like Qt and GTK.
Source: www.technotification.com
15 data science tools to consider using in 2021
Matplotlib is an open source Python plotting library that's used to read, import and visualize data in analytics applications. Data scientists and other users can create static, animated and interactive data visualizations with Matplotlib, using it in Python scripts, the Python and IPython shells, Jupyter Notebook, web application servers and various GUI toolkits.
Source: searchbusinessanalytics.techtarget.com
Top Python Libraries For Image Processing In 2021
Matplotlib is primarily used for 2D visualizations such as scatter plots, bar graphs, histograms, and many more, but we can also use it for image processing. It is effective to get information out of an image. It doesnโ€™t support all file formats.
Source: www.analyticsvidhya.com
Top 8 Python Libraries for Data Visualization
Matplotlib is a data visualization library and 2-D plotting library of Python It was initially released in 2003 and it is the most popular and widely-used plotting library in the Python community. It comes with an interactive environment across multiple platforms. Matplotlib can be used in Python scripts, the Python and IPython shells, the Jupyter notebook, web application...
Source: www.geeksforgeeks.org

Social recommendations and mentions

Based on our record, Matplotlib seems to be more popular. It has been mentiond 114 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.

CrashPlan mentions (0)

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

Matplotlib mentions (114)

  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib โ€” the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review. Nothing unusual. - Source: dev.to / 4 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes itโ€™s easier to spot patterns when you can actually see your data. Pandas works seamlessly with Matplotlib, a popular Python library for creating visualizations. Together, they make it easy to turn raw numbers into clear charts. - Source: dev.to / 7 months ago
  • libmalloc, jemalloc, tcmalloc, mimalloc - Exploring Different Memory Allocators
    We are storing the results in JSON files, which we combine, analyze and visualize using matplotlib in Python. Here's the structure of a benchmark result file:. - Source: dev.to / 7 months ago
  • Building an AI Scoring Agent: Step-By-Step
    NetworkX and Matplotlib were used to visualize the graph structure of the agent. - Source: dev.to / 9 months ago
  • Top 5 GitHub Repositories for Data Science in 2026
    The book introduces the core libraries essential for working with data in Python: particularly IPython, NumPy, Pandas, Matplotlib, Scikit-Learn, and related packages Familiarity with Python as a language is assumed; if you need a quick introduction to the language itself, see the free companion project, Aโ€ฆ. - Source: dev.to / 10 months ago
View more

What are some alternatives?

When comparing CrashPlan and Matplotlib, you can also consider the following products

Backblaze - Backblaze's remote backup automatically backs up your data to our secure datacenter.

Pandas - Pandas is an open source library providing high-performance, easy-to-use data structures and data analysis tools for the Python.

ManageWP - ManageWP is a service for bloggers, site owners and web based companies helping them manage multiple WordPress sites from one dashboard.

NumPy - NumPy is the fundamental package for scientific computing with Python

MiniTool Partition Wizard - As a partition magic alternative, Minitool Partition Wizard is the latest partition manager software which be used to manage partition on Windows 10/8/7/XP and Server 2003/2008/2012.

Seaborn - Seaborn is a Python data visualization library that uses Matplotlib to make statistical graphics.

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