Oracle HeatWave GenAI

Research Brief: Oracle HeatWave GenAI

Oracle HeatWave GenAI is now generally available. The release features the industry’s first in-database large language models (LLMs), automated vector store, scale-out vector processing, and natural language conversations informed by unstructured content.

The release enables enterprises to leverage generative AI with their data without needing AI expertise or moving data to a separate vector database. Available at no extra cost to HeatWave customers, these capabilities enhance data security and performance while reducing costs.

Key features include:

  • In-Database LLMs: Simplify the development of generative AI applications, allowing for data search, content generation, and retrieval-augmented generation (RAG) with HeatWave Vector Store.
  • Automated Vector Store: This enables easy use of generative AI with business documents without data transfer and AI expertise, automating the creation and embedding process.
  • Scale-Out Vector Processing: This technology provides fast and accurate semantic search results using a new VECTOR data type and optimized distance function, enabling efficient parallel processing.
  • HeatWave Chat: A Visual Code plug-in for MySQL Shell, offering a graphical interface for natural language or SQL queries and maintaining context for continuous, accurate conversation.

This Research Brief takes a deeper look at what Oracle announced.

Disclosure: The author is an industry analyst, and NAND Research an industry analyst firm, that engages in, or has engaged in, research, analysis, and advisory services with many technology companies, which may include those mentioned in this article. The author does not hold any equity positions with any company mentioned in this article.