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Scilab VS GetXAPI

Compare Scilab VS GetXAPI and see what are their differences

Scilab

Scilab Official Website. Enter your search in the box aboveAbout ScilabScilab is free and open source software for numerical . Thanks for downloading Scilab!

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0 reviews
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GetXAPI

GetXAPI is the cheapest Twitter API and X API. $0.001 per call returns ~20 tweets ($0.05 per 1,000). Fetch tweets, profiles, followers. Cheapest Twitter & X API alternative.

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0 reviews
Pricing
Freemium Free trial $0.05 (1000 tweets)
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ASocks
Clear, Fast & Unlimited. Residential & Mobile Proxies For Best Price. sponsored
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?

Technical Computing popularity
100% vs 0%
alternatives listed
183 vs 12

Base details

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

Scilab
GetXAPI
Website scilab.org getxapi.com
Pricing —
Freemium Free trial $0.05 (1000 tweets) Official pricing
Company — Startup from the United Arab Emirates · 1 - 9 employees · 2026
Listed in
Technical Computing Numerical Computation Architecture 3D +1
Developer Tools API Tools SaaS Developer APIs +1

About Scilab and GetXAPI

In their own words, as submitted to SaaSHub.

Scilab
GetXAPI

No description of Scilab yet.

GetXAPI is the cheapest Twitter API (X API) for developers and AI agents: pay-per-call data with no subscription and no X developer account. Most endpoints are $0.001 per call (about $0.05 per 1,000 tweets); DMs are $0.002. New accounts get $0.10 in free credits, no card. Read: search, profiles,...

Read more about GetXAPI

Features and specs

What each product offers, as listed by its team.

Scilab 6 features
GetXAPI 5 features
  • Open Source
    Scilab is free and open-source software, allowing users to access the source code and modify it to suit their needs without any cost.
  • Extensive Mathematical Functionality
    Scilab provides a wide range of mathematical functions and capabilities for numerical computation, making it suitable for a variety of scientific and engineering applications.
  • Toolboxes and Modules
    It offers various built-in toolboxes and modules for specialized tasks, such as signal processing, control systems, and optimization, expanding its functionality.
  • Cross-Platform Support
    Scilab runs on different operating systems, including Windows, macOS, and Linux, providing flexibility for users working in diverse environments.
  • Strong Community Support
    A large and active user community means that users can find plenty of support, tutorials, and third-party contributions, easing the learning curve.
  • Integration Capabilities
    Scilab can be easily integrated with other software and tools, such as Modelica for modeling and simulation, enhancing its versatility in different workflows.

Possible disadvantages

  • Performance
    Scilab may not be as performance-optimized as some other numerical computation software, like MATLAB, especially for very large datasets or highly complex calculations.
  • Learning Curve
    While Scilab is powerful, it can be challenging for beginners to master due to its extensive functionality and the need to learn its scripting language.
  • Less Commercial Support
    As open-source software, Scilab does not offer the same level of commercial support or extensive professional resources that are available for some paid alternatives like MATLAB.
  • Documentation Quality
    Although Scilab has a lot of documentation, some users find that it lacks depth or clarity compared to other software, making it harder to find thorough explanations or examples.
  • Graphical User Interface
    The graphical user interface (GUI) of Scilab is not as polished or user-friendly as that of some competitor tools, which can impact user experience.
  • Compatibility Issues
    Interoperability with MATLAB can be limited, potentially causing issues when porting code or collaborating with MATLAB users.
  • API Discovery
    GetXAPI provides a searchable directory of APIs, making it easier for developers to discover and compare available APIs across different industries and use cases.
  • Centralized Information
    The platform aggregates API documentation, endpoints, and details in one place, reducing the time needed to research multiple sources for API information.
  • User-Friendly Interface
    The site is designed to be accessible for developers of varying experience levels, presenting API information in a structured and digestible format.
  • Categorization
    APIs are organized into categories, allowing users to quickly narrow down options based on their specific project needs or industry focus.
  • Free Access
    Basic browsing and searching of API listings is typically free, making it a low-cost resource for developers exploring options before committing to a specific API provider.

Possible disadvantages

  • Limited Depth
    While GetXAPI aggregates basic information, it may lack the in-depth technical documentation, code samples, or SDKs that developers need for actual implementation, requiring them to visit the original API provider's site anyway.
  • Potential Outdated Listings
    API directories can struggle to keep listings current, and some APIs may be deprecated, changed, or no longer available, leading to inaccurate information.
  • Lack of Testing Tools
    Unlike some competing platforms, GetXAPI may not offer built-in API testing, sandbox environments, or interactive consoles to try endpoints directly within the site.
  • Coverage Gaps
    The directory may not include every available API on the market, particularly newer, niche, or less popular APIs, limiting its usefulness for comprehensive research.
  • Dependency on External Providers
    Since GetXAPI is essentially a directory, the quality, reliability, and support for any given API still depends entirely on the third-party provider, not GetXAPI itself.

Analysis

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

Scilab
GetXAPI

Overall verdict

  • Overall, Scilab is a robust and cost-effective alternative to other commercial numerical computation software. Its strengths lie in its flexibility and the support of a large community of users and contributors.

Why this product is good

  • Scilab is considered good by many due to its open-source nature, comprehensive capabilities for numerical computations, and its extensive community support. It offers a wide range of mathematical functions for engineering and scientific applications and is particularly favored for its ability to handle complex data analysis and simulations. Additionally, its compatibility with MATLAB code and its powerful graphical capabilities make it a versatile tool for developers and researchers.

Recommended for

    Scilab is recommended for engineers, scientists, and educators who require a powerful computational tool without the associated costs of commercial software. It is also suitable for students and researchers who are looking to perform complex mathematical modeling and simulations.

Overall verdict

  • I don't have verified, up-to-date information about GetXAPI (getxapi.com) to make a reliable assessment. I cannot confirm its legitimacy, features, pricing, or user reputation, so I'd recommend independent research before using or trusting this service.

Why this product is good

  • No verified data available on this specific platform in my knowledge base
  • Unable to confirm company background, registration, or regulatory status
  • Cannot validate user reviews, complaint history, or trustworthiness signals
  • Details about services offered (e.g., trading, API access, exchange) are unclear without direct verification

Recommended for

  • Users should independently verify the site's legitimacy via domain age checks, WHOIS lookup, and regulatory registration before proceeding
  • Check third-party review sites (Trustpilot, Reddit, forums) for user experiences
  • Confirm SSL certificate, company registration, and physical address if claims are made
  • Consult financial regulatory bodies if it claims to offer trading or investment services
  • Exercise caution with any upfront deposits or personal financial information requests

Videos

Walkthroughs and reviews on video.

Scilab 3 videos + Add
GetXAPI 0 videos + Add

Scilab IPCV 1.2

More videos

  • - Raspberry Pi for Computer Vision with Scilab
  • - Tone Recognition with Scilab and LabVIEW to Scilab Gateway

No GetXAPI videos yet. You could help us improve this page by suggesting one.

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
Scilab
GetXAPI
100% 100%
Technical Computing
0% 0%
0% 0%
APIs
100% 100%
100% 100%
Numerical Computation
0% 0%
0% 0%
Developer Tools
100% 100%

Questions & Answers

As answered by people managing Scilab and GetXAPI.

How would you describe the primary audience of your product?

GetXAPI's answer:

Developers and AI-agent builders who need affordable, reliable Twitter/X data without the cost or setup of the official API. Typical users are indie developers and founders, automation builders (n8n, MCP, Cursor), growth and social-monitoring teams, and researchers collecting tweet datasets.

What makes your product unique?

GetXAPI's answer:

GetXAPI is the cheapest way to read and write Twitter/X data programmatically. Most endpoints cost $0.001 per call (about $0.05 per 1,000 tweets) on a pure pay-per-call model, with no subscription, no developer-account approval, and no platform-level rate limits. You sign up with email, copy a Bearer token, and start calling 50+ endpoints right away.

Why should a person choose your product over its competitors?

GetXAPI's answer:

It is roughly 3x cheaper than twitterapi.io and far cheaper than the official X API for reads, with no monthly minimum, so you only pay for what you use. Unlike the official API there is no developer-account approval and no 15-minute rate-limit windows to engineer around. It also ships ready-made integrations: a public OpenAPI 3.1 spec, an MCP server for Claude and Cursor, and Apify actors.

What's the story behind your product?

GetXAPI's answer:

GetXAPI started after its founder kept overpaying for Twitter/X data through the official API, Apify, and RapidAPI. After spending weeks understanding how those tools work, he built a leaner pay-per-call API that delivers the same reads and writes at a fraction of the cost, with no subscription or developer account. It launched publicly in early 2026 and grew through the developer community.

Which are the primary technologies used for building your product?

GetXAPI's answer:

GetXAPI is a REST API built on Node.js and TypeScript, returning JSON with Bearer-token authentication and a public OpenAPI 3.1 specification. For integration it provides an MCP server (Claude, Cursor, Continue), Apify actors, a Postman collection, and interactive Fern docs.

Who are some of the biggest customers of your product?

GetXAPI's answer:

  • Indie developers and solo founders building Twitter/X features
  • AI agent and automation builders (n8n, MCP, Claude and Cursor workflows)
  • Growth, marketing, and social-monitoring teams
  • Researchers and data teams building tweet datasets

User comments

Share your experience with using Scilab and GetXAPI. For example, how are they different and which one is better?

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Reviews and articles

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

Scilab no reviews yet
GetXAPI no reviews yet
  • 25 Best Statistical Analysis Software
    www.scijournal.org · Aug 2023

    Scilab is a powerful, free, and open-source software widely used by researchers, students, and professionals in various fields such as engineering, mathematics, physics, and more.

  • 7 Best MATLAB alternatives for Linux
    cyanogenmods.org · Apr 2022

    The syntax of Scilab is similar to MATLAB it also provides a source code translator to convert MATLAB code to Scilab.

  • Matlab Alternatives
    www.educba.com · Dec 2020

    Scilab is an open-source similar to the implementation of Matlab. The approximation techniques known as Scientific Computing is used to solve numerical problems. To achieve this, the team of Scilab developers made use...

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