Lower Your Data Management Costs with SAP HANA Cloud
Let’s be completely honest — there is a lingering belief that whatever SAP HANA’s advantages as a data platform (which, of course, are many), it’s still too expensive and is something of a luxury. Some misconceptions also state that SAP HANA it is too niche and encourages businesses to “put everything into memory,” which is extravagant and unnecessary.
We want to deconstruct everything wrong with these misconceptions. No, you shouldn’t run everything in-memory. No, SAP HANA is not a luxury. Yes, SAP HANA is the right platform for the enterprise and it is anything but niche. In recent years, the case against the “SAP HANA is too expensive” argument has grown stronger and stronger. And now, with the introduction of SAP HANA Cloud, the argument is clearer than ever.
Comparing Apples to Apples
The principal way that naysayers have framed their “too expensive” argument over the years has been to make apples-to-oranges comparisons between SAP HANA and other platforms. Comparing an SAP HANA deployment to, say, an Oracle or (more erroneously) a Hadoop deployment is off-base in several important ways.
It’s easy to show that it costs more to deploy an entire enterprise dataset in-memory with SAP HANA than it does to deploy the same dataset on disk with a conventional database. And the difference looks even starker when the SAP HANA environment is compared to Hadoop. But these kinds of comparisons miss several critical points:
SAP HANA is architecturally distinct from conventional databases in several important ways (and even more different from Hadoop.) Its data compression capability, coupled with its ability to reduce duplication of data throughout the enterprise, completely changes the economics of any comparison between platforms. SAP HANA helps to reduce the overall enterprise data footprint, rather than massively expanding it.
Usability of Data
It isn’t just a question of how much it costs to store the data. It’s a question of what you need to do with it. If you are running high-speed transactions and complex analytics that demand real-time results, Hadoop is not going to be able to deliver. An environment that “costs less” but that can’t meet the fundamental needs of the business doesn’t really represent any kind of savings.
The conventional database might have a better chance of meeting those kinds of requirements, but to do so, it will almost certainly be required that the data be tiered between in-memory, high-speed disk access, and slower disk access.
Through Dynamic Tiering, SAP HANA provides a tiered, multi-level, multi-temperature data storage environment for some time. The real comparison would be between such an environment supported by a conventional database and the same environment supported by SAP HANA. That comparison would have to take into consideration, as noted above, SAP HANA’s data compression and other data-footprint-reducing features.
Removing these erroneous comparisons enables a valid analysis that takes into consideration SAP HANA’s performance capabilities, its architectural advantages over other platforms, and its typical deployment (which includes a rational tiering of storage). In light of that kind of analysis, the “cost savings” of using a conventional database or other platform disappear.
Extend to SAP HANA Cloud
Now, the cloud-native version of SAP HANA adds the advantages of cloud economics to the performance, scalability, and flexibility already inherent in SAP HANA. You now have the flexibility to extend your on-premise investments to the cloud, or to deploy a cloud-first strategy.
Multi-Temperature Data Layers
For starters, SAP HANA Cloud has brought the full multi-level, tiered storage architecture into the SAP HANA environment. Now users can manage the full tiered dataset from the cloud with SAP HANA Cloud. The top tier provides real-time, in-memory access to your most critical data.
The Data Lake
Next comes the SAP HANA Cloud data lake. It is a unique data lake environment, built on a database framework that can store large volumes of data for rapid access. In addition to cold data, the data lake can also serve as a repository for large volumes of incoming data such as sensor data from IoT (Internet of Things) systems.
Because of the architecture, data stored in the data lake is ready to go for whatever analytical (or transactional) application needs to access it. Like the SAP HANA in-memory data platform, the data lake provides significant data compression and also helps to reduce unnecessary data duplication of the enterprise.
Breaking Down Silos
Reducing complexity and simplifying operations is one of the key advantages of SAP HANA Cloud over other cloud data management services. The wide range of different databases and storage systems from put application developers or system architects in the same data management dilemma they faced in the last millennium. Namely, data residing in individual silos that are only capable of handling one specialized workload (say, transaction processing) and storage format. SAP HANA Cloud services eliminates these issues by breaking down silos and handling both transactional and analytical workloads.
Flexibility for a High ROI
In addition to providing management of the full data environment, SAP HANA Cloud opens up possibilities that meet the challenges of a data-first world. The flexibility of the cloud enables business to scale their environment with a precision never before experienced. You can build of your existing on-premise investment to increase memory, storage, or computational capability without requiring a permanent investment or commitment. A cloud environment can be scaled up temporarily to meet peak periods of demand, allowing the business to pay only for the additional capacity when needed.
With the promise of these kinds of capabilities, SAP HANA Cloud presents a solution that is not “too expensive” and can help businesses manage their assets more effectively. Far from being a luxury, SAP HANA Cloud ensures your business gets the highest possible return on investment from all its data assets.