Oracle recently introduced enhanced capabilities for its HeatWave technology, aiming to facilitate the use of generative AI within Oracle Cloud Infrastructure (OCI) and Amazon Web Services (AWS). These upgrades, designed to improve the performance and manageability of transactional applications, will also support lakehouse and machine learning applications.
Edward Screven, chief corporate architect at Oracle, highlighted the synergy between the new HeatWave features and generative AI applications. “Some organizations, such as SmarterD, are building new generative AI applications on HeatWave and moving into production in less than a month,” he stated. According to Screven, the availability of HeatWave GenAI on AWS permits users to create AI applications without needing AI-specific expertise, bypassing complex manual integrations and security risks.
The integration of generative AI capabilities is particularly beneficial for companies like SOCOBOX. Hans Ospina, CTO and founder, remarked, “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.”
These capabilities are intended to address a wide array of data types and sources, enhancing functionalities in analytics, transaction processing, machine learning, and generative AI. Specific innovations for AWS include HeatWave GenAI, which develops secure generative AI applications and utilizes in-database large language models (LLMs). Benchmarks indicate considerable price performance improvements over other services available.
HeatWave Lakehouse is another standout feature, enabling rapid insights from structured, semi-structured, and unstructured data in Amazon S3. It claims the top position in performance and price-performance metrics within the industry. Additionally, native JavaScript support allows users to write stored procedures and functions in JavaScript, executing them natively inside HeatWave, enhancing operational efficiency.
Furthermore, HeatWave Autopilot indexing predicts the optimal set of indexes for OLTP workloads, minimizing the complexity of manual indexing. For comprehensive adoption, Oracle has also unveiled multi-lingual support for 27 languages and enhanced optical character recognition (OCR) for similarity searches. Other enhancements include LLM inference batch processing, automatic vector store updates, and newer functionalities supporting the VECTOR datatype in JavaScript.
For OLTP workloads, HeatWave MySQL now offers a hypergraph optimizer for cost-based join optimization, integration with OCI Ops Insights for performance management, and improved data ingestion capabilities. HeatWave Lakehouse, meanwhile, features efficient querying and change propagation functionalities.
Addressing machine learning needs, HeatWave AutoML supports larger models, topic modelling, data drift detection, and semi-supervised log anomaly detection. The free tier option of Oracle’s cloud services now includes HeatWave, providing organizations an opportunity to develop and run small-scale applications equipped with varied functionalities, including analytics and machine learning.
