HeatWave Innovation Rolls on with New Generative AI and Multicloud Capabilities

Rhea-AI Summary

Oracle has announced new HeatWave capabilities for generative AI and multicloud applications. Key highlights include:

1. HeatWave GenAI for AWS customers, offering integrated, automated, and secure generative AI.

2. Vector processing with HeatWave on AWS and OCI, providing 39X better price performance than Snowflake, 96X better than Databricks, and 48X better than Google Big Query.

3. New features for HeatWave on AWS, including GenAI, Lakehouse, native JavaScript support, and Autopilot indexing.

4. Enhancements to HeatWave MySQL, HeatWave Lakehouse, and HeatWave AutoML.

5. HeatWave availability in Oracle Cloud Free Tier, allowing organizations to develop and run small-scale applications using various HeatWave features.

Positive

• HeatWave GenAI offers 39X better price performance than Snowflake, 96X better than Databricks, and 48X better than Google Big Query
• Vector creation with HeatWave is up to 30X faster and 1/3rd the cost of Knowledge Bases for Amazon Bedrock
• HeatWave on AWS enables customers to reduce complexity by replacing up to six AWS services
• HeatWave Lakehouse can query data in object storage at the same speed as database queries without data copying
• HeatWave is now available in the OCI Always Free Service, allowing small-scale application development at no cost

Negative

• None.

Insights

Tech Expert

Oracle's HeatWave innovation marks a significant leap in cloud database technology. The introduction of HeatWave GenAI on AWS demonstrates Oracle's commitment to multicloud strategies, potentially disrupting the market dominance of native AWS services. This move could attract AWS customers looking for integrated AI solutions without the complexity of managing multiple services.

The performance benchmarks are particularly noteworthy: 39X better price performance than Snowflake, 96X better than Databricks and 48X better than Google BigQuery for vector processing. If these figures hold up in real-world scenarios, it could significantly alter the competitive landscape in the cloud data analytics market.

The addition of native JavaScript support and automated features like Autopilot indexing could streamline development processes, potentially reducing time-to-market for new applications and improving overall developer productivity.

Financial Analyst

Oracle's strategic expansion of HeatWave capabilities could have a substantial impact on its market position and financial performance. By offering a comprehensive solution that replaces multiple AWS services, Oracle is positioning itself to capture a larger share of cloud spending from enterprises looking to consolidate their tech stack and reduce costs.

The introduction of HeatWave in the OCI Always Free Tier is a smart move to increase adoption and market penetration. This freemium model could lead to increased paid conversions over time, potentially boosting Oracle's cloud revenue streams. However, investors should monitor the cost implications of offering such powerful capabilities for free.

The multicloud strategy with availability on both OCI and AWS demonstrates Oracle's adaptability to market demands, which could help mitigate risks associated with vendor lock-in concerns among potential customers. This approach may lead to increased customer acquisition and retention rates.

AI Research Analyst

HeatWave GenAI's integration of in-database LLMs and automated vector processing represents a significant advancement in making AI more accessible and practical for businesses. The ability to run LLMs on CPUs rather than specialized hardware could democratize AI adoption by reducing infrastructure costs.

The multilingual support for 27 languages and OCR capabilities expand the potential use cases, making it particularly valuable for global enterprises dealing with diverse data types. This could accelerate the adoption of AI in sectors like legal, healthcare and international business.

The inclusion of features like automatic vector store updates and data drift detection addresses critical challenges in maintaining AI model relevance over time. This focus on operational aspects of AI could significantly reduce the total cost of ownership for AI systems and improve their long-term effectiveness.

However, the true impact will depend on the quality and performance of these AI features in real-world applications compared to specialized AI services offered by competitors.

HeatWave GenAI now provides integrated, automated, and secure generative AI to AWS customers

Vector processing with HeatWave on AWS and OCI offers 39X better price performance than Snowflake, 96X better than Databricks, and 48X better than Google Big Query

LAS VEGAS, Sept. 10, 2024 /PRNewswire/ -- Oracle CloudWorld -- Oracle today announced new HeatWave capabilities, including innovations to help organizations more easily and securely take advantage of generative AI both in Oracle Cloud Infrastructure (OCI) and in Amazon Web Services (AWS). Additional new capabilities help customers quickly and securely implement lakehouse and machine learning applications for a wider variety of use cases, as well as help improve 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. Some organizations, such as SmarterD, are building new generative AI applications on HeatWave and moving into production in less than a month," said Edward Screven, chief corporate architect, Oracle. "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."

"The integration of generative AI in HeatWave is a major leap forward for us," said Hans Ospina, CTO and founder, SOCOBOX. "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."

Organizations applying analytics, transaction processing, machine learning, and generative AI across various data types and sources can leverage new HeatWave capabilities, including:

HeatWave on AWS
AWS customers can reduce complexity by replacing up to six AWS services with HeatWave. New HeatWave capabilities on AWS, which are also available on OCI, include:

• HeatWave GenAI: Helps AWS customers simplify the development of secure generative AI applications at a lower cost. Users can automate vector store creation and vector embedding generation, use in-database large language models (LLMs) running on CPUs or use models from Amazon Bedrock, and have natural language conversations with their documents in Amazon S3. A benchmark shows that vector processing with HeatWave offers 39X better price performance than Snowflake, 96X better than Databricks, and 48X better than Google Big Query. Vector creation with HeatWave is up to 30X faster and 1/3rd the cost of Knowledge Bases for Amazon Bedrock.
• HeatWave Lakehouse: Helps AWS users get faster insights from all their data by querying structured, semi-structured, and unstructured data in Amazon S3 with the industry's best performance and price-performance.
• Native JavaScript support: Enables AWS users to write stored procedures and functions in JavaScript and execute them natively inside HeatWave, for example, to build dynamic content-loading applications using the rich features of JavaScript to process and query data in object storage.
• HeatWave Autopilot indexing: Enables AWS users to predict the optimal set of indexes needed for their OLTP workloads, reducing the time-consuming and complex task of determining the required indexes manually.

HeatWave GenAI
By providing integrated, automated, and secure generative AI, HeatWave GenAI lets developers build new generative AI applications without AI expertise, data movement, or additional cost. New capabilities include:

• Multi-lingual support: Helps developers build global applications with the ability to load documents in 27 languages into HeatWave Vector Store to perform similarity searches and ask questions in various languages.
• Optical Character Recognition (OCR) support: Helps users conduct similarity searches by leveraging HeatWave Vector Store to convert scanned content saved as images into text data that can be analyzed, for example, to detect plagiarism.
• LLM inference batch processing: Helps developers improve application throughput by executing multiple requests simultaneously across the HeatWave cluster.
• Automatic vector store update: Will help developers build applications using the latest data as changes to documents in object storage automatically trigger updates to corresponding vector embeddings.
• JavaScript support: Enables developers to use JavaScript with the VECTOR datatype and invoke HeatWave GenAI from a JavaScript program, for example, to more easily build chatbots accessing enterprise data.

HeatWave MySQL
HeatWave MySQL enables OLTP workloads to leverage the Enterprise Edition features of MySQL Database and delivers unique capabilities, such as Auto Shape Prediction, Auto Thread Pooling, Autopilot Indexing, and in-database JavaScript. New capabilities include:

• Hypergraph optimizer: Enables users to achieve true cost-based join optimization of query plans and improve performance, particularly for complex queries.
• Integration with OCI Ops Insights: Helps administrators uncover performance issues, forecast consumption, and plan capacity using ML-based analytics.
• Bulk ingest: Will enable users to load data into HeatWave MySQL up to 5X faster. As a result, data can be queried sooner, and resources are freed up faster, reducing costs.

HeatWave Lakehouse
HeatWave Lakehouse enables users to query hundreds of terabytes of data in object storage with the best price-performance in the industry. HeatWave Lakehouse can uniquely query data in object storage at the same speed as database queries without the need to copy the data from the object store to the database. New capabilities include:

• Writing results to object storage: Enables users to easily share query results and store them in object storage inexpensively. It also enables developers to use HeatWave for MapReduce applications.
• Automatic change propagation: Will enable users to always query the latest data by automatically detecting data changes in object storage and updating those changes incrementally to HeatWave.

HeatWave AutoML
HeatWave AutoML includes everything users need to build, train, and explain machine learning models within HeatWave at no additional cost. It provides support for classification, regression, anomaly detection, recommender systems, and time series forecasting. New capabilities include:

• Storing and processing larger models: Enables users to train ML models with a richer training data set by increasing capacity to accommodate 4X larger models.
• Topic modeling: Helps users discover insights in large textual data sets by helping them understand key themes in documents, for example, to complete sentiment analysis on social media data.
• Data drift: Helps users determine when to retrain models by detecting the differences between the data used for training and new incoming data.
• Semi-supervised log anomaly detection: Enables users to provide feedback on the results of unsupervised anomaly detection and use this labeled data to help improve subsequent predictions.

HeatWave Available in Oracle Cloud Free Tier
HeatWave is now available in the OCI Always Free Service, which enables organizations to develop and run small-scale applications using HeatWave MySQL, analytics, machine learning, JavaScript, HeatWave Vector Store, and process data in object store. All OCI accounts get access to a standalone HeatWave instance in OCI in their home region, along with 50 GB of storage and 50 GB of backup storage, for an unlimited time. They also receive $300 of credit to use for all eligible OCI services for up to 30 days.

Additional Resources

• Read the technical blog
• Read the Oracle HeatWave GenAI technical brief
• Learn more about Oracle HeatWave

About Oracle
Oracle offers integrated suites of applications plus secure, autonomous infrastructure in the Oracle Cloud. For more information about Oracle (NYSE: ORCL), please visit us at oracle.com.

About Oracle CloudWorld
CloudWorld is where our customers and partners can see the latest innovations in cloud technology, discover methods for getting the most business value from AI today, and explore ways to increase productivity and efficiency through automation. You'll learn from experts and your peers who build and use the applications, cloud infrastructure, databases, developer tools, and AI services that help solve complex business challenges in every industry. Join us to develop new skills and see new capabilities in action. Register now at oracle.com/cloudworld or follow the news and conversation at oracle.com/news and linkedin.com/company/oracle.

Future Product Disclaimer
The preceding is intended to outline our general product direction. It is intended for information purposes only, and may not be incorporated into any contract. It is not a commitment to deliver any material, code, or functionality, and should not be relied upon in making purchasing decisions. The development, release, timing, and pricing of any features or functionality described for Oracle's products may change and remains at the sole discretion of Oracle Corporation.

Forward-Looking Statements Disclaimer
Statements in this article relating to Oracle's future plans, expectations, beliefs, and intentions are "forward-looking statements" and are subject to material risks and uncertainties. Many factors could affect Oracle's current expectations and actual results, and could cause actual results to differ materially. A discussion of such factors and other risks that affect Oracle's business is contained in Oracle's Securities and Exchange Commission (SEC) filings, including Oracle's most recent reports on Form 10-K and Form 10-Q under the heading "Risk Factors." These filings are available on the SEC's website or on Oracle's website at oracle.com/investor. All information in this article is current as of September 10, 2024, and Oracle undertakes no duty to update any statement in light of new information or future events.

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SOURCE Oracle

FAQ

What new generative AI capabilities does Oracle HeatWave (ORCL) offer for AWS customers?

Oracle HeatWave GenAI now provides integrated, automated, and secure generative AI to AWS customers. It includes features like multi-lingual support, OCR support, LLM inference batch processing, automatic vector store updates, and JavaScript support for building AI applications without AI expertise or data movement.

How does HeatWave's (ORCL) vector processing performance compare to competitors?

According to Oracle's benchmark, HeatWave's vector processing offers 39X better price performance than Snowflake, 96X better than Databricks, and 48X better than Google Big Query. Additionally, vector creation with HeatWave is up to 30X faster and 1/3rd the cost of Knowledge Bases for Amazon Bedrock.

What new features does Oracle HeatWave (ORCL) introduce for MySQL in September 2024?

Oracle HeatWave MySQL introduces new features including a hypergraph optimizer for improved query performance, integration with OCI Ops Insights for ML-based analytics, and bulk ingest capability that can load data up to 5X faster.

How does Oracle HeatWave (ORCL) enhance machine learning capabilities in its September 2024 update?

HeatWave AutoML introduces enhancements such as increased capacity to store and process 4X larger models, topic modeling for textual data insights, data drift detection for model retraining, and semi-supervised log anomaly detection for improved predictions.