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The Oracle Ecosystem Gets Cloudy

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It will take time until the market fully embraces cloud. “In its current iteration, connecting to Oracle’s cloud and on-premises databases is complicated, oftentimes requiring multiple means of configuration from multiple vendors,” said Paul Nashawaty, director of product marketing and management for Progress. “While there has been a great deal of hype about cloud adoption, the lion’s share of enterprises are still utilizing on-premises databases. However, as cloud technology continues to improve, companies will have more incentive than ever to begin migration, including cloud economics, security, and geographically distributed environments.”

Cloud may fit well with specific use cases. “From our discussions with customers, Oracle’s cloud offerings seem to be most applicable to Oracle’s pre-built applications like Financials or CRM,” said Monte Zweben, co-founder and CEO of Splice Machine. However, he added, while “it represents just another option on how to deploy those applications, customers still do not seem happy with the high cost of Oracle software. We have not heard of anybody having Oracle host its database for custom-built or third-party applications.”

There may even be too much push from Oracle to move to the cloud. “Oracle’s marketing shift toward cloud solutions has left customers in a state of limbo,” according to Marc Caruso, CTO for Data Intensity. “Because of the compensation structure, sales representatives are now heavily incented to push cloud products, even if they may not be the best fit for a customer’s particular situation. Customers are in a quandary over whether to upgrade now, or wait until the cloud applications are more stable and robust.” He added that there is “a wide range of maturity across Oracle’s cloud applications from the very mature—Oracle CPQ Cloud, Oracle Service Cloud—to the recently launched Oracle BI Cloud and Oracle EPM Cloud.”

Big data—along with the analytics associated with it—is also shaking the market to its foundations. As is the case with all other enterprise technology spaces, the Oracle ecosystem is seeing the effects of the consumerization of technology, coupled with the emergence of big data, said Vishal Anand, director of PwC’s Oracle Practice—cloud, big data, and data management. “Facebook and Google have transformed technology, and it’s a transformation that corporations want to emulate. It’s driven by the end user, because at the end of the day, the end user gets on their mobile phone, picks an app, and it’s downloaded. A lot of the changes that are occurring have a lot to do with application development. Therefore, data needs to align with that as well.”

This means great changes are on the horizon for partners, vendors, and enterprises that comprise the Oracle ecosystem—especially as it relates to the vendor’s foundational database system. “Oracle’s involvement in the big data and cloud spaces has notably affected business operations and technology demands,” said Nashawaty. “As a result, more and more companies are looking to include nontraditional—yet potentially very valuable—data in all business intelligence.”

The rise of big data and demands for widespread access and analytics have created the need for faster and more responsive environments, often beyond what relational databases can deliver. “From an architectural standpoint, it was pretty standard to have a relational database at the back end,” said Anand. “People were still poking around on some sort of middleware caching capabilities. Because transaction size has gotten bigger in terms of volume, the typical database response time no longer suffices, based on hard drives.” Instead, Anand is seeing rising adoption of in-memory, solid-state technology and object-oriented caching environments. The database itself is kept “as a source of truth of information, just in case you need historical data, as well as providing persistency at the back end.”

The drive to data analytics is creating a major sea change in the way data is managed and processed. “As data sizes continue to explode, the classic ETL model of moving data from an operational database to an analytic database has become untenable,” said Mike Skubisz, vice president of product management at Deep Information Sciences. “The time required to move data prevents analytics from executing against fresh data and has given rise to the idea of a hybrid transactional and analytic platform. These systems need to provide high performance and scale for both read- and write-intensive workloads.”

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