Kinetica Utilizes Natural Language Processing with ChatGPT for SQL Database Queries
Kinetica, a provider of relational databases for real-time analytics and online analytical processing, is integrating the power of OpenAI’s ChatGPT for natural language processing, enabling developers to establish SQL queries via natural language. According to Kinetica, ChatGPT turns natural language into Structured Query Language (SQL), and users can enter inquiries that send an API call off ChatGPT, producing an SQL syntax for generating results. The ChatGPT interface is incorporated into the front end of Kinetica Workbench and is built to answer any query in natural language about proprietary data sets in the database.
The company announced that the ChatGPT integration is available at no cost in its free developer edition, which can be installed on any laptop or PC. Kinetica Workbench infers from the query and maps it to the correct column, allowing users to understand the intent of the question precisely. Moreover, the database is competent in answering up-to-date, real-time analytical queries since it continually ingests streaming data. SQL-92 is used as a query language in Kinetica, as well as PostgreSQL and MySQL, and supports text search, time series analysis, location intelligence, and graph analytics that can now be accessed via natural language.
Vectorisation Boosts Query Speed with GPU and CPU
The company claims that vectorisation enhances the speed with which its relational database processes queries, including fixed-size blocks called vectors that store data and can perform parallel query operations. The vectorised query engine processes multiple data elements simultaneously, resulting in a faster query execution on a smaller compute footprint. In Kinetica, vectorisation is possible due to the combined use of graphical processing units (GPUs) and CPUs.
Bradley Shimmin, Chief Analyst at Omdia Research, said that vendors in the business intelligence market have made more progress in integrating natural language querying (NLQ) while Kinetica is one of the first database firms to integrate ChatGPT or generative AI features within a database. However, Shimmin also noted that Kinetica's use of ChatGPT for natural language querying is not strictly speaking an actual database querying.
Kinetica says it is open to collaborating with other large language model (LLM) providers when new use cases arise, and disclosed that it derives more than half of its revenue from US defense agencies like NORAD. Its clients are from the connected car space, finance, telecom, logistics, and the entertainment sector.
