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What is ThanoSQL?

ThanoSQL is an integrated platform that is capable of query and AI(artificial intelligence) modeling both structured and unstructured data1 with only SQL2. You can apply the functions of RDB (Relational Database)3, AI, and Big Data Platform within one platform and significantly reduce inefficiencies that occur during AI-based digital transformation.

  • ThanoSQL can query both structured and unstructured data with SQL alone and enables rapid AI modeling.
  • By replacing the lambda architecture4-based unstructured big data platform with one ThanoSQL, development, deployment, and operation can be done in a single process.
  • Based on big data processing and distributed parallel processing technology, data processing is more than twice as fast as before.

Advantage of ThanoSQL

AI-based digital transformation requires a wide range of knowledge and technologies, including various programming languages, frameworks, and big data platforms based on lambda architecture, and continuous insight discovery. These complex requirements gradually increase the difficulty of technology implementation and the complexity of the process, which in turn requires a lot of manpower and time to develop, deploy, and operate.

The diagram below is a data engineering ecosystem map that shows more than 60 technologies at a glance for building data science and big data analytics systems.


Against this situation, ThanoSQL

  • Integrate multiple development/operational platforms, programming languages, and frameworks into one, dramatically accelerating development and eliminating inefficiency.

With ThanoSQL, you don't need to know many of the technology stacks in the figure above, and you can continue to produce better results, faster than developers (or data engineers) who know all of the technology stacks.

Experience the innovative results of ThanoSQL now

  1. Data without an identifiable structure or architecture. Text, speech, and images are primarily applicable and do not follow a predefined data model, making them unsuitable for relational databases. However, this flexibility is scalable and unrestricted. Properly analyzed, unstructured data can be used for various applications and provide valuable business intelligence insight. 

  2. It is a special purpose programming language designed to process data from the Relational Data Base Management System(RDBMS) and is also called a query language. 

  3. It refers to a database based on a relational data model. Relational data models represent all data in a two-dimensional table as one of the necessary ways to organize the data. Typically, you can only handle structured data. 

  4. Because of the difficulty in analyzing a large amount of data in real-time, this method combines a data table that can be acquired in real-time with a batch table that has been calculated in advance at a particular time so that a certain amount of real-time analysis is possible even for large volumes of data. 

Last update: 2024-06-05