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Which is more popular?
Based on our record, Maxima
seems to be more popular. It has been mentioned
27 times
since March 2021.
social mentions
27 vs 0
Technical Computing popularity
100% vs 0%
Base details
Website, pricing, platforms and company facts side by side.
Open-source Maxima is freely available and open-source, allowing users to access, modify, and distribute the software without any cost.
Symbolic Computation Maxima specializes in symbolic computation, providing robust tools for algebraic manipulations, differentiation, integration, and equation solving.
Customizability As an open-source software, Maxima is highly customizable, and users can modify the source code or write their own functions to extend its capabilities.
Documentation Maxima comes with extensive documentation, including a comprehensive manual and numerous tutorials, which can aid both beginners and advanced users.
Integration with Other Tools Maxima can be integrated with other software tools and languages such as Python (via SymPy), providing flexibility and additional functionality for complex computations.
Possible disadvantages
User Interface The default user interface of Maxima is less polished compared to commercial alternatives, which may affect the user experience, especially for beginners.
Performance While suitable for many tasks, Maxima may not perform as efficiently as some specialized commercial software for very large or complex computations.
Learning Curve Due to its depth and the nature of symbolic computation, there can be a steep learning curve for new users who are not already familiar with similar tools or mathematical concepts.
Community Support As an open-source project, support primarily comes from the user community, which may not always be as responsive or comprehensive as professional, paid support services.
Updates and Maintenance Maxima updates and maintenance depend on community contributions, which can sometimes lead to less frequent updates or delayed fixes for bugs compared to commercial software.
Lightweight C++ implementation cppq is written in modern C++ and designed to be a minimal, efficient task queue library, making it a good fit for performance-sensitive applications where the overhead of scripting language runtimes is undesirable.
Redis-backed reliability Built on top of Redis as the message broker, cppq benefits from Redis's persistence, atomic operations, and wide adoption, giving the queue system durability and the ability to survive process restarts.
Inspired by proven design (asynq) The library's architecture mirrors the popular Go asynq task queue, so it inherits a well-thought-out API design for task enqueueing, retries, and worker processing patterns that have already been validated in production systems.
Native integration for C++ projects For teams already working in a C++ codebase, cppq allows adding background job processing without needing to introduce a separate service written in another language (like Go or Python), simplifying the technology stack.
Open source and inspectable Being open source on GitHub, developers can review the source code, modify it for custom needs, and contribute improvements, which offers transparency not available with closed-source queueing solutions.
Possible disadvantages
Limited maturity and battle-testing Compared to established task queue libraries like Sidekiq, Celery, or asynq itself, cppq is a newer and smaller project with less real-world production usage, which may translate into undiscovered bugs or edge cases.
Smaller community and ecosystem Because it has far fewer users and contributors than mainstream task queue systems, finding community support, third-party tutorials, or pre-built integrations is more difficult.
Documentation gaps As a smaller project, cppq may have less comprehensive documentation compared to major task queue frameworks, requiring developers to read source code directly to understand advanced features or edge-case behaviors.
C++ build and dependency complexity Using cppq requires managing C++ build toolchains and dependencies (such as a Redis client library), which can be more cumbersome than installing a package via pip or npm in other ecosystems.
Fewer built-in features and tooling cppq likely lacks the extensive ecosystem tooling of more mature queues, such as web-based monitoring dashboards, extensive metrics/observability integrations, or advanced scheduling features found in more established solutions.
Analysis
An editorial look at what each product does well and who it suits.
Maximacppq
No analysis of Maxima yet.
Overall verdict
cppq is a lightweight, Redis-backed distributed task queue for C++ inspired by Go's popular 'asynq' library. It's a good choice for developers who need a simple, dependency-light job queue system in C++ without the overhead of larger enterprise messaging systems, though it's a smaller, less battle-tested project compared to mature alternatives.
Why this product is good
Simple and lightweight design makes it easy to understand and integrate into existing C++ projects
Built on Redis, a well-established and reliable backend for queue storage, giving it a solid foundation
Inspired by asynq (a proven Go library), so the design patterns and task queue semantics are based on a well-thought-out model
Open source on GitHub, allowing developers to inspect, modify, and contribute to the code
Good fit for projects already using Redis, minimizing the need for additional infrastructure
Straightforward API for enqueueing and processing background jobs in C++ applications
Recommended for
C++ developers needing a background job/task queue without adopting a heavyweight message broker
Projects already using Redis as part of their infrastructure
Small to medium-sized applications requiring asynchronous task processing
Teams comfortable working with less mainstream or smaller open-source libraries and willing to contribute or debug issues themselves
Developers familiar with asynq (Go) looking for a similar pattern in C++
Prototyping or hobby projects where a minimal task queue solution is sufficient
Another alternative to MATLAB is Maxima which is a computer algebra system (CAS) for manipulation of symbolic and numerical expressions including differentiation, integration, Laplace transformation, linear algebraic...
Another alternative of Matlab is Maxima which was inspired by the legendary Algebra system Macsyma. It is a system used for manipulating numerical expressions such as Taylor series, Laplace transformations, Vectors,...
I've been using Maxima since my undergraduate (over 10 years), now with Ubuntu20.04 lts, I become a newbie of SageMath. For a small project (both symbolical and numerical), in particular, student lab activities,...
Recommendations tracked on public social media and blogs since March 2021.
Maxima27 mentionscppq0 mentions
Integral Calculator
I think the really neat piece of software behind this is maxima (https://maxima.sourceforge.io/), a rather influential computer algebra system of ancient lineage still in use today in more place than you might think.
- Source: Hacker News
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over 2 years ago
In the maxima computer algebra system[1] which was ancestrally based on lisp it has a single quote operator[2] which delays evaluation of something and a "double quote" (which acually two single quotes rather than an actual double quote)...
- Source: Hacker News
/
over 2 years ago
True or False
Use wxmaxima, a free and open-source computer algebra system:.
Source:
almost 3 years ago
Mathematica has characterized the cutting edge in specialized processing—and gave the chief calculation environment to a large number of pioneers, instructors, understudies, and others around the globe.
Scilab Official Website. Enter your search in the box aboveAbout ScilabScilab is free and open source software for numerical . Thanks for downloading Scilab!
Julia is a sophisticated programming language designed especially for numerical computing with specializations in analysis and computational science. It is also efficient for web use, general programming, and can be used as a specification language.
MATLAB
Wolfram Mathematica
GNU Octave
Scilab
Sage Math
Julia
Mathcad
