
RaimaDB, an embedded time series database that can be used for Edge and IoT devices, can run in-memory. It is a lightweight, secure, and extremely powerful RDBMS. It has been field tested by more than 20 000 developers around the world and has been deployed in excess of 25 000 000 times.
RaimaDB is a high-performance, cross-platform embedded database optimized for mission-critical applications in industries such as IoT and edge computing. Its lightweight design makes it ideal for resource-constrained environments, supporting both in-memory and persistent storage options. RaimaDB offers flexible data modeling, including traditional relational models and direct relationships through network model sets. With ACID-compliant transactions and advanced indexing methods like B+Tree, Hash Table, R-Tree, and AVL-Tree, it ensures data reliability and efficiency. Built for real-time processing, it incorporates multi-version concurrency control (MVCC) and snapshot isolation, making it a robust solution for applications demanding speed and reliability.
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Gaffa is a REST API built for web scraping and browser automation, allowing developers to run real, full browsers at scale with a single API call. It removes the difficulty of managing headless browser frameworks, rotating proxies, CAPTCHA solving, and scaling infrastructure, all of which are handled automatically.
JavaScript-heavy and dynamic websites render exactly as they would for a human visitor by default. Beyond standard scraping, Gaffa supports AI-driven structured data extraction (extract data into a defined schema without writing CSS selectors), screenshot and PDF capture, infinite-scroll and form-filling automation, and clean Markdown conversion for feeding webpages directly into LLM and RAG pipelines.
A rotating residential proxy network keeps access reliable across regions, and a credit-based pricing model means teams pay only for the browser time and bandwidth they actually use. Gaffa is designed for AI engineers, data teams, and developers who want production-grade web data extraction without having to build and maintain their own infrastructure.
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BotDetect CAPTCHA
The BotDetect™ CAPTCHA generator serves as a non-intrusive security solution for forms, utilizing a combination of techniques that are simple for users yet challenging for automated systems, effectively blocking unwanted submissions. Additionally, it offers an audio CAPTCHA option to ensure accessibility for visually impaired users, allowing compliance with WCAG and Section 508 standards. In light of years of Google’s aggressive exploitation of its search monopoly and a corresponding campaign of misinformation regarding CAPTCHAs, the competitive landscape has dwindled to just two significant players. Over its initial decade, BotDetect distinguished itself by providing a diverse array of CAPTCHA image and audio algorithms, all of which were user-friendly while the random selection of these algorithms rendered automated bypass attempts exceedingly difficult. This innovative approach has solidified BotDetect's reputation as a leader in CAPTCHA technology, ensuring both security and accessibility.
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TextCaptcha
The TextCaptcha service offers a straightforward JSON or XML API over HTTP that delivers text-based CAPTCHA challenges. The primary component is the textual question posed to the user, while the valid responses are represented as MD5 hashes of the correct answers converted to lowercase; this allows for verification against user responses. Text-based CAPTCHAs are generally more user-friendly for individuals with visual impairments compared to traditional image-based options like ReCAPTCHA. Additionally, they are advantageous when challenges need to be communicated through text-only mediums such as SMS or IRC. However, a significant drawback of text CAPTCHAs is that they tend to convey more information than distorted images, making them potentially easier to decipher. With the rise of advanced parsing technologies like Wolfram Alpha, even relatively simple logic challenges can now be tackled with greater ease by automated systems. This evolution poses ongoing challenges for the effectiveness of text-based CAPTCHA systems in maintaining security against bots.
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