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Confluence VS NumPy

Compare Confluence VS NumPy and see what are their differences

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All-in-one work management platform for team collaboration. featured
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Confluence logo Confluence

Confluence is content collaboration software that changes how modern teams work

NumPy logo NumPy

NumPy is the fundamental package for scientific computing with Python
  • Confluence Landing page
    Landing page //
    2024-08-12
  • NumPy Landing page
    Landing page //
    2023-05-13

Confluence features and specs

  • Integration with Atlassian Ecosystem
    Confluence integrates seamlessly with other Atlassian products like Jira, Bitbucket, and Trello, making it an excellent choice for teams already using these tools.
  • Real-time Collaboration
    Confluence offers real-time collaboration features, including editing, commenting, and task assignments, which enhance team productivity and communication.
  • Document Management
    With version control, easy-to-use templates, and a robust search function, Confluence excels in document management and organization.
  • Customization Options
    It provides numerous customization options including themes, templates, and plugins to suit the specific needs of different teams and projects.
  • Enterprise-Grade Security
    Confluence offers advanced security features such as data encryption, user permissions, and compliance with industry standards, making it suitable for enterprises.

Possible disadvantages of Confluence

  • Complexity for New Users
    The abundance of features can make Confluence overwhelming for new users, creating a steep learning curve.
  • Cost
    Confluence can be expensive, particularly for larger teams or when advanced features and additional plugins are required.
  • Performance Issues
    Users have reported performance issues, such as slow load times, especially with large documents or extensive use of add-ons.
  • Customization Can Be Time-Consuming
    While customization is a strength, it can also be time-consuming to set up and maintain, particularly for non-technical users.
  • Limited Offline Access
    Confluence's functionality is limited without an internet connection, which can be a drawback for teams needing constant access to documents and collaboration tools.

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.

Analysis of Confluence

Overall verdict

  • Confluence is generally considered a good option for teams seeking a comprehensive collaboration and documentation platform. Its strengths lie in its integration capabilities, customization options, and user-friendly interface. However, for smaller teams or those with simpler needs, it may be more complex and feature-rich than necessary.

Why this product is good

  • Confluence by Atlassian is a popular collaboration tool known for its robust features that facilitate team communication, documentation, and project management. It integrates seamlessly with other Atlassian products like Jira, making it an excellent choice for software development teams. Its flexibility allows users to create and organize content using customizable templates and spaces, supporting both structured and unstructured data. Additionally, Confluence offers a range of plug-ins and integration options, enhancing its functionality even further.

Recommended for

    Confluence is particularly recommended for medium to large-sized organizations, software development teams, and businesses that utilize other Atlassian products. It's ideal for groups that require advanced documentation features, seamless integrations, and strong collaboration tools to optimize their workflows.

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.

Confluence videos

+ Add

Confluence Cloud Product Demo 2019

More videos:

  • Demo - Atlassian Confluence Demonstration Video
  • Review - (2016) Introduction to Confluence: Create, share, and collaborate on projects in one place

NumPy videos

+ Add

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

Category Popularity

0-100% (relative to Confluence and NumPy)

Confluence

NumPy

Project Management
100 100%
Project Management
0% 0
Data Science And Machine Learning
0 0%
Data Science And Machine Learning
100% 100
Task Management
100 100%
Task Management
0% 0
Data Science Tools
0 0%
Data Science Tools
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 Confluence and NumPy

Confluence Reviews

Top 10 Notion Alternatives for 2025 and Why Teams Are Choosing Ledger
Confluence is great for documentation-heavy teams, especially when paired with other Atlassian products like Jira. But as a standalone collaboration tool, it lacks the fluidity and connected workflows that many modern teams need.
Source: www.ledgerteams.com
11 Popular Knowledge Management Tools to Consider in 2025 
Confluence is a web-based collaboration tool developed by Atlassian. It allows teams to create, store, and organize information in one place. This can include project documentation, meeting notes, how-to guides, and company policies.
Source: knowmax.ai
Best Gitbook Alternatives You Need to Try in 2023
Confluence is a collaboration tool from Atlassian that focuses on remote-ready teams that need to organize content. It has a built-in editor and allows for version control, making it easy to track changes and collaborate with team members. Confluence also has a wide range of templates and add-ons available, allowing users to add all types of documents for a knowledge base....
Source: www.archbee.com
Best 25 Software Documentation Tools 2023
Confluence is the perfect way to collaborate with your team. Is a web-based team collaboration and documentation tool. It helps teams work together, share information and create documentation in a centralized and organized manner. It's a platform that allows the team to create, edit, and organize content such as documents, pages, blogs and multimedia.
Source: www.uphint.com
Introduction to Doxygen Alternatives In 2021
Confluence is a tool in the innovation stack category of project management. In Confluence, it is easy to capture the details which is often lost in email inboxes and shared network drives due to the fact that it is easy to browse, update, as well as use.
Source: www.webku.net

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.
Source: www.analyticsvidhya.com
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

Social recommendations and mentions

Based on our record, NumPy seems to be more popular. 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.

Confluence mentions (0)

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

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

What are some alternatives?

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

Trello - Infinitely flexible. Incredibly easy to use. Great mobile apps. It's free. Trello keeps track of everything, from the big picture to the minute details.

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

Notion - All-in-one workspace. One tool for your whole team. Write, plan, and get organized.

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

Slack - A messaging app for teams who see through the Earth!

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

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