Software Alternatives & Startups

Matplotlib VS Riskified

Compare Matplotlib VS Riskified and see what are their differences

Matplotlib

matplotlib is a python 2D plotting library which produces publication quality figures in a variety...

Rating
0 reviews
Pricing
Open source
Riskified

eCommerce fraud prevention solution and chargeback protection guarantee for online merchants. Find out how we can help your company boost revenue from online sales using our machine-learning powered eCommerce fraud protection software.

Rating
0 reviews
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.

Which is more popular?

Based on our record, Matplotlib seems to be more popular. It has been mentioned 114 times since March 2021.

social mentions
114 vs 0
Data Science And Machine Learning popularity
100% vs 0%
alternatives listed
240+ vs 69

Base details

Website, pricing, platforms and company facts side by side.

Matplotlib
Riskified
Website matplotlib.org riskified.com
Pricing
Open source
Company — Startup from the United States · 500 - 999 employees · 2012
Listed in

Features and specs

What each product offers, as listed by its team.

Matplotlib 6 features
Riskified 5 features
  • 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

  • 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.
  • Chargeback Guarantee
    Riskified offers a chargeback guarantee on approved transactions, meaning if a fraudulent transaction is approved by their system, Riskified will cover the cost of the chargeback, providing a financial safety net for merchants.
  • Increased Approval Rates
    Merchants often see increased approval rates because Riskified's advanced algorithms and machine learning models are tailored to accurately identify genuine customers, allowing more legitimate transactions to be approved.
  • Global Solution
    Riskified supports a wide range of payment methods and currencies, making it suitable for merchants with a global presence and varying customer demographics.
  • Seamless Integration
    The platform offers seamless integration with major e-commerce platforms and payment gateways, reducing the time and effort required for merchants to set up and begin protecting transactions.
  • Advanced Analytics
    Riskified provides merchants with detailed analytics and reporting tools, helping them understand transaction patterns, assess risk, and optimize their operations.

Possible disadvantages

  • Cost
    The service can be relatively expensive for smaller businesses, especially those with thin margins, as the pricing model typically involves a fee per transaction or a percentage of the transaction value.
  • Complexity
    For businesses without a dedicated team for fraud prevention, understanding and leveraging all the features and data that Riskified provides can be complex and time-consuming.
  • Dependence on External Provider
    Relying on Riskified for fraud prevention places a critical aspect of the business's operations in the hands of an external provider. Any downtime or service issues with Riskified could directly impact transaction processing.
  • False Positives
    While Riskified aims to minimize false positives, there is always a risk that legitimate transactions may be wrongly declined, which can lead to customer dissatisfaction and potential loss of sales.
  • Customization Limits
    Some merchants may find that the level of customization available in Riskified's fraud prevention algorithms and workflows does not fully meet their unique business needs or preferences.

Analysis

An editorial look at what each product does well and who it suits.

Matplotlib
Riskified

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.

Overall verdict

  • Riskified is generally considered a good solution for businesses looking to enhance their fraud detection and prevention capabilities. It is especially recommended for online retailers who wish to strike a balance between reducing fraud and maintaining a seamless customer experience.

Why this product is good

  • Riskified is a well-regarded eCommerce fraud prevention platform that leverages machine learning and big data to identify fraudulent transactions and boost conversion rates. It offers comprehensive solutions for chargeback protection, payment optimization, and account security. Many businesses appreciate its ease of integration, detailed analytics, and the ability to increase approval rates while minimizing fraud-related losses.

Recommended for

  • E-commerce companies
  • Online marketplaces
  • Retail businesses with significant online presence
  • Merchants dealing with high volumes of transactions
  • Businesses seeking advanced analytics for fraud insights

Videos

Walkthroughs and reviews on video.

Matplotlib 1 video + Add
Riskified 3 videos + Add

Learn Matplotlib in 6 minutes | Matplotlib Python Tutorial

Riskified Educational Webinar: Automating The Fraud Review Process (Summer Boot Camp - 2nd Webinar)

More videos

  • - Riskified Educational Webinar: Optimal Manual Review (Summer Boot Camp - 3rd Webinar)
  • - Riskified : Nanoleaf case study

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
Matplotlib
Riskified
0% 0%
100% 100%
100% 100%
0% 0%
0% 0%
100% 100%

User comments

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Reviews and articles

External articles and on-site reviews we used to compare the two products.

Matplotlib no reviews yet
Riskified no reviews yet

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Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Matplotlib 114 mentions
Riskified 0 mentions
  • The soul file
    In February, an AI agent named MJ Rathbun submitted a pull request to matplotlib — the Python plotting library used by half the scientific computing world. Scott Shambaugh, a volunteer maintainer, rejected it. Standard code review.... - Source: dev.to / 7 months ago
  • How to Analyze CSV Files with Python and Pandas
    Numbers are useful, but sometimes it’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... - Source: dev.to / 10 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 / 11 months ago

View more

Tracking Riskified since Mar 2021.

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