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Turbo Data Laboratories: Pioneers of Future Generation Database Systems

Internet of things (IoT), Artificial Intelligence (AI), Virtual reality (VR), and Machine learning technologies generate an enormous amount of big data in the backdrop, which is beyond conventional relational database systems to handle. Turbo Data Laboratories (TDL) is one such organization, who has been challenging the basic theory of Database system from last two decades.
After extensive R&D over the years, Turbo Data has created three main state-of-the-art technologies, namely, Zap-In, Zap-Over and Zap-Mass.
Shinji Furusho, President, TDL, an alumnus the University of Tokyo, founded the company in the year 2000. With more than worldwide 100 patents to his name, the founder has played an instrumental role in the evolution of the Turbo Data Laboratories and nurturing open initiatives. The organization is a market leader and at the peak of success, due to their revolutionary database engine technology, today.
Shinji says, “We are highly committed and determined to offer the best of the best ultra-high-speed database solutions to the businesses across diverse sectors.
For his outstanding contribution to the industry, Shinji Furusho is honoured with numerous awards and recognition, including the prestigious Nikkei BP Technology Award.
Unconventional and Ultra-Modern Solutions   
Zap In- Big Data’s Spreadsheet with RDB Functions
Zap-In technology is specifically developed to enable big data’s spreadsheet with Relational Data Base (RDB) functions. Technically speaking, the basic functionality of spreadsheet is to respond immediately to every operation of every data, however, the existing acceleration mechanism- Index technology, can’t achieve these mainly due to two reasons.
Firstly it requires memory or storage for it. So, you cannot attach it to every field. And secondly, it requires very limited preconditions to use. In addition to that, an Index doesn’t work for subsets.
Therefore, Zap-In comes to the rescue; it abandoned index technology and made the impossible, possible, by converting outside data into Zap-In TR (Table Representation) format. And after that, every DB operation uses Zap-In TR as inputs, makes Zap-In TR as outputs.
As every data is in the format of Zap-In TR, the technology covers each and every data, which is unlikely in Index technology. This is because, TDL has developed more than one hundred of excellent algorithms for Zap-In to cover almost all DB operations, due to which it can perform all the operations very quickly. As a result, Zap-In runs up to 100,000 times faster than existing technologies, available in the industry. TDL has also licensed Zap-In patents to SAP and several other companies.
Due to Zap In’s extraordinary processing capability, it has been used at JAXA (Japan Aerospace Exploration Agency), and at JNFL (Japan Nuclear Fuel Limited).
Zap Over- Big data’s Open Library Distributed over the Internet
Zap-Over is basically developed, to enable a free combination of Big data’s libraries for browsing/searching/mashing up by PCs or iPhones. Each library is up to about 1 trillion rows and usually is stored in a NAS, which is distributed over the Internet.
Zap-Over, enables the users to browse smoothly, search them and pick billions of exact hit results in sub-second, which is beyond conventional technology.
Let’s understand Zap-Over, with an example. Imagine a scenario where you are browsing and searching an encyclopedia. You search and access/read the required page/s only, rather than going through all the pages of encyclopedia. This is possible because every item is in sorted form. But this ideal situation is only probable when the number of sort keys is one. When a database table has multiple items, like “name” and “address”, it becomes impossible to put both of them in sorted form. And this ideal situation is impossible, when you use multiple encyclopedias at a same time.
Zap-Over has the competence to mitigate all these problems. Therefore any combination of libraries of Big data distributed over the Internet is sorted in every field. Meaning, a user can browse and search them anytime. The technology is revolutionary in nature and hence, has been used in National Tax Agency (Tokyo Region) to seek worldwide money laundering.
Zap Mass- A Theory for Huge Big data’s Relational and Spreadsheet like Operations
Japan has a rich history and culture with regards to academic developments since centuries. For instance, Takakazu Seki, also recognized as ‘Japan’s Newton,’ was a well-known mathematician, who published about ‘Determinants’ in 1674, which were nine years before Gottfried Leibniz, a German polymath and philosopher who worked in the same field. Shinji aspires to bring 1st Turing Award to Japan by it.
Zap-Mass is typically a theory, designed to be one important kind of cloud side system, like Supercomputer or Quantum computer.
The core of Zap-Mass theory is a basic algorithm named ‘Global L-Operation.’ The Global L-Operation is loaded with fantastic features like, Independence from calculation order, multiple symmetries, and divisibility/connectivity. Therefore, the massive parallel system which is designed by Zap-Mass, can do preemptive multitasking, which is not easy for supercomputers.
The performance of sorting will be easily raised more than 1,000,000 times than current database systems. An interesting fact about Zap-Mass is, one typical application of it, is making Google’s full-text search indexes.
Unfolding the Future Roadmap
The recent study estimates that the global market share of big data and its allied technology is expected to reach approximately $54 billion by the year 2020.
In future, Zap-Over is planned to be used in Japan’s challenging project to open Big data gathered by artificial satellites owned by the Japanese government; the data size is expected to be 10 PB / year.
“Going forward, we intend to proceed with advanced technological development to deliver even better innovative, world-class products and solutions. We at present have set targets for a number of newly developed technologies and strategizing for commercializing them. Our idea is to strengthen and intensify our alliances with various partner firms and augments our internal structures to ensure that consumers around the globe can utilize even better products,” says Shinji.
Source :-The 10 Best Performing Big Data Solution Providers 2018