Software Alternatives, Accelerators & Startups

NumPy VS Simple Analytics

Compare NumPy VS Simple Analytics and see what are their differences

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NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python

Simple Analytics logo Simple Analytics

The privacy-first Google Analytics alternative located in Europe.
  • NumPy Landing page
    Landing page //
    2023-05-13
  • Simple Analytics Landing page
    Landing page //
    2022-09-05

Simple Analytics gives you insights into the performance of your website without ever collecting personal data, with a clean interface, and simple integration. GDPR, CCPA and, PECR compliant because we don't handle personal data and set no cookies.

Simple Analytics

$ Details
paid Free Trial $9.0 / Monthly (Max 10,000 page views)
Release Date
2018 September

NumPy features and specs

  • Performance
    NumPy operations are executed with highly optimized C and Fortran libraries, making them significantly faster than standard Python arithmetic operations, especially for large datasets.
  • Versatility
    NumPy supports a vast range of mathematical, logical, shape manipulation, sorting, selecting, I/O, and basic linear algebra operations, making it a versatile tool for scientific and numeric computing.
  • Ease of Use
    NumPy provides an intuitive, easy-to-understand syntax that extends Python's ability to handle arrays and matrices, lowering the barrier to performing complex scientific computations.
  • Community Support
    With a large and active community, NumPy offers extensive documentation, tutorials, and support for troubleshooting issues, as well as continuous updates and enhancements.
  • Integrations
    NumPy integrates seamlessly with other libraries in Python's scientific stack like SciPy, Matplotlib, and Pandas, facilitating a streamlined workflow for data science and analysis tasks.

Possible disadvantages of NumPy

  • Memory Consumption
    NumPy arrays can consume large amounts of memory, especially when working with very large datasets, which can become a limitation on systems with limited memory capacity.
  • Learning Curve
    For users new to scientific computing or coming from different programming backgrounds, understanding the intricacies of NumPy's operations and efficient usage can take time and effort.
  • Limited GPU Support
    NumPy primarily runs on the CPU and doesn't natively support GPU acceleration, which can be a disadvantage for extremely compute-intensive tasks that could benefit from parallel processing.
  • Dependency on Python
    Since NumPy is a Python library, it depends on the Python runtime environment. This can be a limitation in environments where Python is not the primary language or isn't supported.
  • Indexing Complexity
    Although NumPy's slicing and indexing capabilities are powerful, they can sometimes be complex or unintuitive, especially for multi-dimensional arrays, leading to potential errors and confusion.

Simple Analytics features and specs

  • Privacy-focused
    Simple Analytics does not collect personal data, ensuring compliance with privacy laws like GDPR and CCPA. This approach appeals to users concerned about data privacy.
  • Ease of Use
    The platform prides itself on a user-friendly interface, making analytics accessible for individuals with varying levels of technical expertise.
  • No Cookies
    By eliminating the need for cookies, Simple Analytics reduces the complexity of compliance and improves user trust.
  • Transparent Pricing
    Offers straightforward pricing without hidden fees, which benefits small to medium-sized businesses looking for cost-effective solutions.
  • Quick Setup
    Setting up Simple Analytics is a quick process, often taking just a few minutes, reducing the time and effort required to begin tracking site data.
  • Lightweight Script
    The tracking script is lightweight, ensuring that it does not significantly affect website loading times, thus maintaining a good user experience.

Possible disadvantages of Simple Analytics

  • Limited Features
    Compared to more comprehensive platforms like Google Analytics, Simple Analytics offers fewer features and customization options, which may not satisfy advanced users.
  • Basic Reporting
    The reporting capabilities are basic and may not provide in-depth insights that large enterprises or data-driven teams may require.
  • No Integration with Ad Services
    Simple Analytics lacks built-in integrations with advertising services like Google Ads, potentially complicating the tracking of campaign performance.
  • Smaller User Community
    Given its niche market focus, the platform has a smaller user community, which can make it harder to find peer support or community-driven solutions.
  • Less Mature Ecosystem
    Unlike older platforms, Simple Analytics may lack integrations with a wide range of third-party tools and services, limiting its flexibility.
  • Cost
    While the pricing is transparent, it can still be seen as relatively high for the features offered, especially when compared to free alternatives like Google Analytics.

Analysis of NumPy

Overall verdict

  • Yes, NumPy is considered good. It is a foundational library in the Python ecosystem for numerical computing and is used globally by researchers, engineers, and data scientists.

Why this product is good

  • NumPy is widely regarded as a good library because it offers fast, flexible, and efficient array handling that is integral to scientific computing in Python. It provides tools for integrating C/C++ and Fortran code, useful linear algebra, random number capabilities, and a vast collection of mathematical functions. Its array broadcasting capabilities and versatility make complex mathematical computations straightforward.

Recommended for

  • Scientists and researchers working with large-scale scientific computations.
  • Data scientists engaged in data analysis and manipulation.
  • Engineers and developers needing performance-optimized mathematical computations.
  • Educators and students in STEM fields.

Analysis of Simple Analytics

Overall verdict

  • Simple Analytics is a good choice for users who prioritize privacy and simplicity in their web analytics tools. It provides sufficient insights for basic website analytics needs without overwhelming users with too much data or complex features.

Why this product is good

  • Simple Analytics is often praised for its privacy-focused approach. It does not collect personal data, which appeals to users and businesses concerned about privacy and compliance with data protection regulations like GDPR. The platform offers an easy-to-understand interface with essential analytics metrics, making it accessible to users without a technical background. Additionally, Simple Analytics is lightweight, which means it doesn't slow down websites as much as other analytics tools might.

Recommended for

    Simple Analytics is recommended for small to medium-sized businesses, bloggers, and website owners who need straightforward analytics and value privacy. It’s particularly suitable for those looking to comply with privacy regulations without compromising on user data protection.

NumPy videos

Learn NUMPY in 5 minutes - BEST Python Library!

More videos:

  • Review - Python for Data Analysis by Wes McKinney: Review | Learn python, numpy, pandas and jupyter notebooks
  • Review - Effective Computation in Physics: Review | Learn python, numpy, regular expressions, install python

Simple Analytics videos

Fathom, simple analytics. A Google Analytics alternative | Privacy & Simplicity focused! 🎯

More videos:

  • Review - Seriously Simple Analytics Review
  • Review - Seriously Simple Analytics Review
  • Demo - Why we created Simple Analytics

Category Popularity

0-100% (relative to NumPy and Simple Analytics)
Data Science And Machine Learning
Analytics
0 0%
100% 100
Data Science Tools
100 100%
0% 0
Web Analytics
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 NumPy and Simple Analytics

NumPy Reviews

25 Python Frameworks to Master
SciPy provides a collection of algorithms and functions built on top of the NumPy. It helps to perform common scientific and engineering tasks such as optimization, signal processing, integration, linear algebra, and more.
Source: kinsta.com
Top 8 Image-Processing Python Libraries Used in Machine Learning
Scipy is used for mathematical and scientific computations but can also perform multi-dimensional image processing using the submodule scipy.ndimage. It provides functions to operate on n-dimensional Numpy arrays and at the end of the day images are just that.
Source: neptune.ai
Top Python Libraries For Image Processing In 2021
Numpy It is an open-source python library that is used for numerical analysis. It contains a matrix and multi-dimensional arrays as data structures. But NumPy can also use for image processing tasks such as image cropping, manipulating pixels, and masking of pixel values.
4 open source alternatives to MATLAB
NumPy is the main package for scientific computing with Python (as its name suggests). It can process N-dimensional arrays, complex matrix transforms, linear algebra, Fourier transforms, and can act as a gateway for C and C++ integration. It's been used in the world of game and film visual effect development, and is the fundamental data-array structure for the SciPy Stack,...
Source: opensource.com

Simple Analytics Reviews

Top 10 AI Data Analysis Tools in 2024
Simple Analytics is a revolutionary web analytics platform that prioritizes user privacy and transparency above all else. Developed as an ethical alternative to data-hungry giants like Google Analytics, Simple Analytics offers a refreshingly lightweight and user-friendly solution for tracking website metrics without compromising on data protection. With its unwavering...
Source: powerdrill.ai
Privacy-oriented alternatives to Google Analytics
Simple Analytics was my original second contender for the analytics of this blog. The $19 a month starting plan with 100k pageviews is on the more expensive side, but their yearly deal gets you a better price than Fathom at just $9 a month.
Lightweight alternatives to Google Analytics
One is the minimalist Simple Analytics product, which is a cloud-based tool created by solo developer Adriaan van Rossum; it has a clean-looking interface with only the few key metrics, similar to Plausible. Another is Fathom, which was open source initially, but the current version is proprietary (although the company hopes to start maintaining the open-source code base...
Source: lwn.net

Social recommendations and mentions

Based on our record, NumPy should be more popular than Simple Analytics. It has been mentiond 119 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.

NumPy mentions (119)

  • Building an AI-powered Financial Data Analyzer with NodeJS, Python, SvelteKit, and TailwindCSS - Part 0
    The AI Service will be built using aiohttp (asynchronous Python web server) and integrates PyTorch, Hugging Face Transformers, numpy, pandas, and scikit-learn for financial data analysis. - Source: dev.to / 5 months ago
  • F1 FollowLine + HSV filter + PID Controller
    This library provides functions for working in domain of linear algebra, fourier transform, matrices and arrays. - Source: dev.to / 9 months ago
  • Intro to Ray on GKE
    The Python Library components of Ray could be considered analogous to solutions like numpy, scipy, and pandas (which is most analogous to the Ray Data library specifically). As a framework and distributed computing solution, Ray could be used in place of a tool like Apache Spark or Python Dask. It’s also worthwhile to note that Ray Clusters can be used as a distributed computing solution within Kubernetes, as... - Source: dev.to / 9 months ago
  • Streamlit 101: The fundamentals of a Python data app
    It's compatible with a wide range of data libraries, including Pandas, NumPy, and Altair. Streamlit integrates with all the latest tools in generative AI, such as any LLM, vector database, or various AI frameworks like LangChain, LlamaIndex, or Weights & Biases. Streamlit’s chat elements make it especially easy to interact with AI so you can build chatbots that “talk to your data.”. - Source: dev.to / 10 months ago
  • A simple way to extract all detected objects from image and save them as separate images using YOLOv8.2 and OpenCV
    The OpenCV image is a regular NumPy array. You can see it shape:. - Source: dev.to / 10 months ago
View more

Simple Analytics mentions (26)

  • This Next.js blog template is awesome.
    Multiple analytics options including Umami, Plausible, Simple Analytics, Posthog and Google Analytics. - Source: dev.to / 8 months ago
  • Awesome-no-code-tools
    Simple Analytics - Simple, clean, and friendly analytics. - Source: dev.to / 11 months ago
  • SaasRock v0.5.0 - Cookie consent and built-in Analytics
    SaasRock does not intend to invent the wheel, there are great analytics solutions out there, both free and powerful. But SaasRock’s main goal is to have everything you need when building SaaS applications, at least in a minimal way. - Source: dev.to / almost 3 years ago
  • Italian watchdog bans use of Google Analytics
    Regarding forbidden countries, it’s not forbidden in the Netherlands, yet. They will announce a verdict in a form of a report by the end of 2022 [1]. To give people an option and pink something else over Google Analytics, I have built an alternative, Simple Analytics [2]. It doesn’t use cookies or any form of tracking and you get still the useful data that 80% of the website owners need. [1]... - Source: Hacker News / almost 3 years ago
  • Italian watchdog bans use of Google Analytics
    It is. Most startups in the EU have to use more and more businesses in the EU. The selection is little, so way more changes to succeed if your EU based and serve both markets. I run Simple Analytics [1], which is a privacy-first analytics business from the Netherlands. I see a lot of business from the EU just because we are from the EU as well. [1] https://simpleanalytics.com/?ref=hn. - Source: Hacker News / almost 3 years ago
View more

What are some alternatives?

When comparing NumPy and Simple Analytics, you can also consider the following products

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

Plausible.io - Plausible Analytics is a simple, open-source, lightweight (< 1 KB) and privacy-friendly web analytics alternative to Google Analytics. Made and hosted in the EU, powered by European-owned cloud infrastructure 🇪🇺

OpenCV - OpenCV is the world's biggest computer vision library

Fathom Analytics - Simple, trustworthy website analytics (finally)

Scikit-learn - scikit-learn (formerly scikits.learn) is an open source machine learning library for the Python programming language.

Google Analytics - Improve your website to increase conversions, improve the user experience, and make more money using Google Analytics. Measure, understand and quantify engagement on your site with customized and in-depth reports.