Fuel MS SQL Server 2017 with Intelligent Data Automation
Posted in tech
If data is the lifeblood of the modern enterprise, databases are the heart that powers the machine. We’ve blogged previously about how Primary Data leverages NFS v4.2 to transparently manage data across heterogeneous storage, according to policy. With Microsoft SQL Server 2017, enterprises can now run these databases on Linux, enabling enterprisesto make use of DataSphere’s machine learning data management. Let’s take a closer look at some ways DataSphere can enhance Microsoft SQL Server databases.
Optimize Database Performance
With DataSphere, admins can rest assured that their SQL Server databases are getting the performance they need to meet SLAs. DataSphere improves SQL Server databases through:
- Native data access: DataSphere moves administration (metadata) out of the data path, so applications directly access storage devices containing the data, rather than passing through a gateway or agent.
- Dynamic load balancing: DataSphere monitors and rebalances data to ensure databases are always meeting IT-defined objectives for performance. If requests begin to contend for resources that threaten these objectives, DataSphere automatically rebalances workloads across storage in the global namespace without application disruption, and without IT intervention required.
Smart Storage Utilization Through Data Tiering
DataSphere can automatically tier data across heterogeneous storage resources to meet IT-defined objectives for performance, protection, and price. This means expensive storage will no longer be filled with cold data, even as enterprises seamlessly automate archival to off- and on-premises cloud/object stores. IT also can confidently meet performance and availability SLAs, while dramatically reducing the need to overprovision. This can lead to potentially millions of dollars in savings. To learn just how big these savings can be, see this blog on our non-invasive Data Profiler tool.
Automating the Most Tiresome Tasks
IT spends far too much time performing two key tasks: performing storage migrations for hardware upgrades and running fire drills to address storage hot spots. DataSphere enables enterprises to perform migrations automatically and non-disruptively, slashing migration project time from weeks or months down to hours. As mentioned above, the DataSphere machine learning metadata engine also proactively addresses hot spots before they ever impact end users. This can makestorage performance-based fire drills a thing of the past.
With DataSphere, admins can ensure Microsoft SQL Server 2017 databases will always have the resources to meet business’s performance and availability requirements, even as they improve storage utilization to free budget, all while reducing IT workload to free time for more strategic tasks. To learn more about how DataSphere can boost your business, connect with us at email@example.com.