Oracle Exadata

The Oracle Exadata Database Machine is a combined compute and storage system marketed for running Oracle Database software. Exadata debuted in 2008 as the first in Oracle Corporation's family of "Engineered Systems".) Oracle Corporation releases new generations of Exadata roughly once a year.

Exadata combines scale-out compute servers, scale-out storage servers, InfiniBand networking and specialized software, packaged in one or more hardware racks, with various sizing options. Exadata compute servers use Intel Xeon processors or SPARC and the Oracle Linux operating system to run Oracle Database software. Exadata storage servers use Intel Xeon processors to perform block storage functions and also run application software to offload data-intensive database processing into storage closest to the data.

As of October 2015^[update], Exadata was available in the Oracle Cloud as a subscription service, also known simply as the "Exadata Service". Databases deployed in this service include all the features and options of Oracle Database Enterprise Edition. Similarly, all Exadata features and capabilities are included in this service. Oracle databases in the Exadata Service are 100% compatible with databases deployed on-premises, which enables customers to transition to the Cloud with no application changes. Oracle Corporation manages this service – including hardware, network, Linux software and Exadata software –, while customers have complete ownership of their databases.

Exadata is designed to run any Oracle Database workload or mix of workloads.

Long running requests, characterized by data warehouse queries, reports, batch jobs and analytics, are reputed to run many times faster compared to a conventional, non-Exadata database server. Customer references often cite performance gains of 10x or greater. Analytics workloads can also use the Oracle Database In-Memory option on Exadata for additional acceleration. Exadata’s "Hybrid Columnar Compression" feature is intended to reduce the storage consumption of data warehouses and archive data as well as increase performance by reducing the amount of I/O.

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