HeatWave update boosts AI capabilities on Oracle & AWS

Oracle unveiled new functionalities for its HeatWave, aiming to assist organisations in leveraging generative AI more efficiently and securely within Oracle Cloud Infrastructure (OCI) and Amazon Web Services (AWS). The enhancements also aim to facilitate the implementation of lakehouse and machine learning applications, while improving the performance and manageability of transactional applications.

"Our track record of delivering powerful new HeatWave capabilities that are automated, integrated, and secure now extends to AI," said Edward Screven, chief corporate architect at Oracle. "Some organisations, such as SmarterD, are building new generative AI applications on HeatWave and moving into production in less than a month. To enable more customers to take advantage of our innovations, including HeatWave GenAI with in-database LLMs, we are making them available natively on AWS. This enables AWS users to build rich generative AI applications without the need for AI expertise, without complex manual integrations and troubleshooting, and without the security risks and costs of moving their data to separate services."

Hans Ospina, CTO and founder of SOCOBOX, highlighted the integration's significance. "The integration of generative AI in HeatWave is a major leap forward for us. By bringing in-database LLMs, automated vector processing, AutoML, and lakehouse into our workflows, we can now deliver powerful AI-driven insights and applications without the overhead of external tools. This comprehensive approach not only simplifies our operations but also ensures real-time, cost-effective solutions that resonate with the demands of our customers."

The latest HeatWave capabilities are designed to support a spectrum of data types and sources, potentially benefitting users involved in analytics, transaction processing, machine learning, and generative AI. The new features are available on both Oracle Cloud Infrastructure (OCI) and AWS.

Specific innovations to HeatWave on AWS include:

• HeatWave GenAI: This supports the development of secure generative AI applications, automating vector store creation and embedding generation, and utilising in-database large language models (LLMs). A benchmark shows significant price performance improvements compared to other services.
• HeatWave Lakehouse: Offers faster insights from data by querying structured, semi-structured, and unstructured data in Amazon S3, claiming the best performance and price-performance metrics in the industry.
• Native JavaScript support: Enables AWS users to write stored procedures and functions in JavaScript and execute them natively inside HeatWave.
• HeatWave Autopilot indexing: Predicts the optimal set of indexes for OLTP workloads, reducing the complexity of manual indexing.

Further enhancing HeatWave GenAI, Oracle has introduced multi-lingual support for 27 languages, optical character recognition (OCR) for similarity searches, LLM inference batch processing, automatic vector store updates, and JavaScript support for the VECTOR datatype.

HeatWave MySQL has also been updated to improve OLTP workloads with the introduction of a hypergraph optimizer for cost-based join optimization, integration with OCI Ops Insights for performance management, and faster data ingest capabilities.

The HeatWave Lakehouse component is designed to offer efficient querying of vast amounts of data in object storage, boasting unique features like writing results to object storage and automatic change propagation.

HeatWave AutoML caters to users' machine learning needs, offering support for larger models, topic modelling, data drift detection, and semi-supervised log anomaly detection.

HeatWave is now accessible through Oracle's cloud free tier, allowing organisations to develop and run small-scale applications with various functionalities including analytics, machine learning, and JavaScript support.