HeatWave Lakehouse lets you query data in object storage with unmatched performance and price-performance—and automatically build, train, and explain machine learning (ML) models. It’s available on Oracle Cloud Infrastructure (OCI), Amazon Web Services (AWS), and Microsoft Azure.
Watch the replay of Chief Corporate Architect Edward Screven’s Oracle CloudWorld keynote: “Build Generative AI Applications—Integrated and Automated with HeatWave GenAI.”
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Nucleus Research analysts interviewed multiple organizations using HeatWave and reported significant operational improvements, including a hundredfold boost for hybrid OLTP/OLAP queries.
HeatWave is a scale-out data processing engine optimized to query data in object storage. You can query structured data, semi-structured data in JSON format, and unstructured documents with HeatWave Vector Store.
Price-performance is significantly better.
Automate the pipeline to build, train, deploy, and explain ML models using data in object storage and MySQL Database, without moving the data to a separate ML cloud service and at no additional cost.
HeatWave Lakehouse processes data in a variety of file formats, including CSV, Parquet, Avro, JSON, and exports from other databases. You can query data in object storage and optionally combine it with transactional data in MySQL databases. With HeatWave Vector Store, you can upload and query unstructured documents. Data loaded into the HeatWave cluster for processing is automatically transformed into the HeatWave in-memory format, and object storage data isn’t copied to the MySQL database. You can also take advantage of HeatWave AutoML, a built-in feature that automates the pipeline to build, train, and explain ML models using data in object storage, the database, or both. There’s no need to move the data to a separate ML cloud service, and there’s no need to be an ML expert.
“HeatWave Lakehouse scales out very well for loading data from object storage and for running queries on object store. The load time and the query times are nearly constant as the size of the data grows and the HeatWave cluster size grows correspondingly. This scale out characteristic of HeatWave Lakehouse for data management is key to efficiently processing very large amounts of data.”
—Henry Tullis, Leader, Cloud Infrastructure and Engineering, Deloitte Consulting
“Data is growing exponentially and so is the amount of data we store in our data lake. The ability to use standard MySQL syntax to query data across our database and object storage to get real-time insights is very important for Natura. This opens up new opportunities to explore and could represent new competitive advantages if we can analyze all this data faster than our competition.”
—Fabricio Rucci, Solution Architect at Natura &Co
“HeatWave Lakehouse allows us to easily and quickly load data on object storage into HeatWave and combine it with MySQL data for analysis.”
—Takashi Kinoshita, Chief Producer, e-Book Division, NTT SOLMARE Corporation
“Organizations looking for the best value in the cloud data lakehouse landscape must seriously consider HeatWave Lakehouse.”
“The ability of HeatWave to load and query data on such a massive number of nodes in parallel is the first in the industry.”
“For HeatWave Lakehouse to deliver record performance for both loading data and querying data is an unprecedented innovation in cloud data services.”
“With HeatWave Lakehouse, Oracle is presenting MySQL customers on AWS and Microsoft Azure with a proposition they may not be able to refuse.”
“HeatWave Lakehouse can simplify the life of data management professionals and should improve the customer experience.”
“Simply put: HeatWave Lakehouse enables you to stay ahead of the competition by taking swift action on meaningful business insights.”
“The HeatWave team has out-innovated the industry, providing five different core database use cases in a single database, which gives CxOs the peace of mind to have one database that can do it all—a truly universal database.”
“HeatWave Lakehouse takes customers to a new level of capabilities: being able to query heterogeneous data across data warehouses and data lakes at petabyte scale using the familiar SQL syntax, while beating popular competitors at query performance, load times, and cost efficiency.”
Experience HeatWave Lakehouse at your own pace with step-by-step instructions.
Learn how to query hundreds of terabytes of data in various file formats in object storage using HeatWave Lakehouse. Discover how simple this process can be with HeatWave Autopilot.
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Start this lab about winning the race with HeatWave LakehouseLearn from experts as they demonstrate how to use HeatWave Lakehouse in different scenarios.
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