Artificial Intelligence (AI) and Big Data share a symbiotic relationship, with Big Data acting as the catalyst for the emulation of human problem-solving capabilities and the advancement of AI decision-making processes.

AI learns from data to make decisions, predictions, or recommendations based on the results of processing large volumes of data.

It encompasses a suite of computer algorithms specifically designed to extract knowledge from massive datasets, facilitating the generation of innovative ideas.

These algorithms are categorized into two groups:

• the AI Engine, which includes algorithms for Big Data formatting and processing (such as optimization, sorting, searching, filtering, grouping, deduplication, aggregation, analytics, and visualizations), and
• the AI decision manager, encompassing algorithms like machine learning, natural language processing, computer vision, deep learning, and high-value insight generation.

We are proud to introduce our pioneering achievement: the Megadata Web (MDW).

The primary goal of MDW's intelligent platform is to significantly accelerate Big Data processing, unlocking endless possibilities for its utilization in millions of professional Web applications. With its super-fast performance, MDW olso is positioned as a world-leading AI engine in the industry.

Within a few days, we can demonstrate that our Big Data AI Engine, MDW, significantly outperforms any similar products globally, including Microsoft Excel, Google Sheets, and others.

If existing AI engines are likened to internal combustion engines, then Megadata Web can be aptly described as a rocket engine.

To optimize data processeng for AI applications, we have developed highly efficient data formats that dramatically reduce memory usage for storage and transmission.

MDW is poised to revolutionize and streamline the entire process of AI and Web application development, leading to substantial cost reductions.

Our advanced data processing algorithms, including sorting, searching, filtering, grouping, deduplication, and aggregation, can handle millions of records much faster than any other existing technologies.

Implemented using standard web technologies like JavaScript, HTML, and CSS, these innovative data formats and algorithms empower AI-driven Big Data processing on various devices, from servers to laptops, tablets, and mobile devices, significantly enhancing Web user decision-making and control, resolving server overload problems, and boosting the speed of data-driven Web applications.

MDW also revolutionizes AI processing by facilitating the distribution of computation from servers to Web client devices.

This approach

• enables server-accelerated parallel processing,
• reduces hardware resource requirements,
• enhances the scalability of Web-based AI applications,
• minimizes bandwidth demands and server connectivity dependencies,
• processes large data volumes offline on client devices, and
• enhances AI decision-making and knowledge generation.

MDW stands as a unique innovation in the current landscape. Discover how MDW can streamline data analysis, optimize AI decision-making processes, and help to deliver actionable insights.

Step into the future of AI by experiencing MDW today!

• User: The individual who uses the web application.
• Client: Part of the application program located in the browser on the user's computer. The client retrieves data for the user from the server, a computer that stores and processes this data.
• Bandwidth: The speed of data delivery in the network between the client and server.
• Offline data processing: The ability of the client to operate inside the browser without server support and even without an internet connection.
• Big data (or Megadata): A term used to describe an overwhelming amount of data, such as tables with millions of records. It's a popular phrase used in the U.S. for the past few years to describe this volume of data.
• Responsive design: A web application implementation that can run on both mobile devices and stationary web devices, such as regular computers.

Currently, many popular JavaScript libraries (frameworks) have been created to simplify and accelerate the development process of Web applications. However, these libraries were not designed to efficiently process big data. As a result, most web applications become slow, complex, and require continuous server support. Despite the availability of powerful, multi-processor computers for every web client, big data web business applications do not leverage these abundant resources due to four major limitations in popular web technologies:

• Slow delivery of large data volumes, which is particularly critical for devices with lower bandwidth.
• Performance limitations on the client side, as browsers can process less data and are slower than servers.
• Restrictions on user computer memory.
• Inability of the client to process data offline within the browser.

We've devised solutions to address all these challenges by decentralizing big data processing on the Web.

In essence, we've engineered an advanced client side data processing engine for AI, prioritizing simplicity, usability, performance, and maximum functionality, while mitigating the inherent issues found in other solutions. We:

• Developed compact data representation to expedite data delivery.
• Achieved quantum leap performance in data processing, capable of handling up to 16,000,000 records on the client and sorting 1,000,000 records in less than one second.
• Created an advanced, compact data format to circumvent memory restrictions on client devices.
• Devised a method for seamless offline data processing.

Our technology provides a AI business application with all the necessary features and intuitive controls for processing big data. It is customizable, straightforward, transparent, light, and intuitive. For “desktop” web users, we benefit them with even more processing power for having a computer with a bigger monitor, more RAM, and a faster processor.

Most AI business applications process big data on servers. We can shift this to the client instead of delegating it to an overloaded server. Thousands of user computers can simultaneously simplify and accelerate the whole application and hence, not rely on the number of server processors available to the users.

Our technology is compatible with all standard browsers (e.g. Chrome, Firefox, Edge, Safari, etc.) and can be integrated easily and seamlessly into any existing web application.

It is fully implemented, debugged, and being installed on a variety of Internet client/server applications.

By eliminating navigation across multiple screens, Megadata Web significantly boosts the responsiveness of the application being used. The average execution time for Megadata Web sorting in different browsers (not IE*) for 1,000,000 records is 1 second!

Technology has dramatically increased, by up to 10,000 times, the amount of data/information that can be delivered onto just a single Web page.

Through the use of our unique data-compacting methods, users will never again see the ubiquitous, unproductive query response: "first 20 of 4,732 records" on their Web browsers.

Megadata Web reduces, by up to 98%, the redundant and unnecessary network traffic associated with current database querying methods.

This translates into increased network capacity for future expansion, and lower maintenance and MSP expenses.

• 24/11/2021: Lead Management - GT Leads, (site)
• 28/09/2021: Contact Management - GT Contacts, (site)
• 27/07/2021: Scheduling system - TomsJS Scheduler, (site)
• 15/05/2021: Logic synthesis system - George Toms synthesis site
• 22/08/2019: Codon Usage Calculator - Margo
• 03/01/2018: WYSIWYG - (What You See Is What You Get) Editor WYSIWYG

All AI Web applications that process data can be benefit from Megadata Web in many directions, including:

1. Significantly Greater Processing Speed
2. Ability to Process Large Volumes of Data
3. Off-line Data Processing Capability
4. Minimized Bandwidth Usage
5. Reduced Memory Requirements
6. Compact Data Formats
7. Advanced Data Processing Algorithms
8. Quantum Leap Screen Rendering Performance
9. Support of Responsive Design Objectives by Placing All Data and Controls “above the fold”
10. Advanced “toolkit” of Features:
• Navigation, scrolling
• Sorting, searching, filtering
• Totaling
• Reporting
• Exporting
• Linking, mapping, e-mailing
• Editing, replacing, adding, deleting
• Undo, start over
• Save, save all
• Drag & drop
• Cell & Table customization
• Hierarchical column grouping
• WYSIWYG Editor

Megadata Web is fully implemented, debugged, and being tested on a variety of AI Internet client/server applications.

It is easy to implement:

• Compatible and interoperable with all standard browsers (e.g. Chrome, Firefox, Edge, Safari, Opera, Vivaldi, Internet, etc.)
• Integrates seamlessly with 3rd party server databases, middleware platforms, Operating Systems and technologies (e.g., .NET, PHP, Java, Node.js…).
• Requires no additional client-side software or plug-ins

Please watch demos of some products based on Megadata Web:

• "Microsoft Excel 2019 vs Megadata Web" (Management of 1,000,000 records on Laptop)
• Download Microsoft Excel file "Customers" with 1,000,000 records in XLSX format
• Download file "Computers" with 1,000,000 records in CSV format
• Download file "Computers" with 100,000 records in CSV format
• Processing of 5,000,000 records on Samsung
• Processing ag-Grid example on Phone Samsung (3,000,000 records), on Chrome (4,000,000 records), and on Safari (5,000,000 records).
• The superior processing capabilities of MDW are evident in the following videos, reflecting MDW benchmarks compared, purely for context, to those same specific features in Microsoft’s Excel 2011 running on a laptop with 16GB of RAM.
• "Alisa - 15M+" (Management of 15,728,625 records)
• "Anastasia - 15M+" (Management of 15,728,625 records)
• Computer Sale (Searching 50,000 record inventory)
• Advanced Computer Sale (Searching 1,000,000 record inventory)
• VCF File Viewer Alyona (Processing 72+ GB VCF file)
• Motif Finder Anjela (Serching 20 motifs - some of them represent up to 2^45 patterns - in chromosome #1 (234.3 MB).)
• DNA Codon Usage Calculator Margo (234.3 MB Fasta Secuence)
• "Wikipedia data table" (Processing of 8,007,840 records on MacBook Pro)
• "Wikipedia data table" (Processing of 8,007,840 records on phone)

• Features
• Functionality
• Demos
• Applications
• Benefits
• Competitors
• Memorandum
• White Paper

• March 05, 2024: Megadata Web technology licensed to advanced gate-level synthesis company GT synthesis LLC
• November 09, 2018: Megadata Web President and CTO George Toms on 7CTOs meeting in Las Vegas,
• February 24, 2017: Megadata Web makes quantum leap forward for fast and secure computer data processing and analysis. » Read more

• For Details and Licence please contact: 
• Phone:  USA: +1 (858) 699-8940
• E-mail:   n@megadataweb.com