Category: Compute

Users who choose to migrate workloads to the cloud prefer to do so without modifying application code and without being required to learn new methods for managing data. Ideally they are seeking a cloud service with like-for-like functionality, and management similar to their on-premises infrastructure. The goal is to accelerate migration and deployment in the […]

Users face challenges in their digital transformation journey involving the migration of data across various platforms, on-premises file systems, and other cloud services. When using other cloud providers, scenarios arise where the seamless transfer of data becomes essential. Whether executing a one-time data transfer or integrating it into a scheduled workflow, minimizing business downtime is […]

Over time, Enterprises may need to undertake operations or make modifications to their data as part of general data management, to address changing business needs, or to comply with evolving data-management regulations and best practices. As datasets being generated, stored, and analyzed continue to grow exponentially, the need for simplified, scalable, and reproduceable data management […]

Given the ubiquity of digital payments, cutting-edge fintech solutions hinge on seamless and highly available real-time transaction processing. Invariably, this needs the support of a performant, reliable, and secure datastore. And after considering technical requirements, fintech companies know that regulatory and compliance auditing never takes a back seat. Enterprise AWS customer Marqeta needed all of […]

Customers host their SAP HANA environments on AWS to run their business-critical processes, such as financial planning, data analytics, and supply chain management. Reliably backing up data in SAP HANA is paramount for users to restore the database in the event of disruptions and urgent business needs. To reliably back up SAP HANA, SAP documentation […]

Companies from different industries use data to help their Artificial Intelligence (AI) and Machine Learning (ML) systems make intelligent decisions. For ML systems to work well, it is crucial to make sure that the massive datasets used for training ML models are of the highest quality, minimizing noise that can contribute to less-than-optimal performance. Processing […]

Many organizations generate large quantities of data locally, including digital imagery, sensor data, and more. Customers require local compute and storage to ingest and enable real-time predications based on their data, and often preprocess this data locally before transferring to the cloud to unlock additional business value such analysis, reporting, and archiving. Automating transfers to […]

Data, the lifeblood of any modern organization, is rarely static. For high-performance applications and workloads, enterprises need the ability to run operations on massive amounts of data, including modifying the data as is necessary for each use case, to further accelerate processing. This could include modifying uploaded images with a watermark, changing the bitrate of […]

When managing a large volume of data in a storage system, it is common for data duplication to happen. Data duplication in data management refers to the presence of multiple copies of the same data within your system, leading to additional storage usage as well as extra overhead when handling multiple copies of the same […]

Business continuity and disaster recovery plans include having a backup strategy for application workloads, whether on-premises or in Cloud. Furthermore, organizations need efficient methods to actively monitor their data protection posture and detect any failure for remediation while meeting the required recovery time objective (RTO) and recovery point objective (RPO) for the business. One efficient […]