Bridging the Memory-Storage Gap to Accelerate Fast Data Analytics
Recorded Sep 20 12:00 am
About this Webinar
The convergence of analytical and transactional workloads, through a unified fast storage and memory infrastructure, is giving way to a new breed of fast data architectures that support real-time analytics and just-in-time data science. To enable this vision, organizations are capitalizing on recent innovations in fast storage that combine volume, velocity, and variety facets of big data all in one data tier. The combination of in-memory data grids and storage-class memory solutions (such as Intel Optane SSD/NVMe) delivers performance that removes the need for competing operational and analytical strategies for accessing data.
In-memory data grids that leverage multi-tiered storage with SCM empower businesses with the capability of unlocking high-value insights from real-time and historical data. In this webinar, we discuss the forces driving this insight-centric trend as well as reference architectures using Apache Spark and GigaSpaces XAP to address particular design challenges for streaming analytics, fast data lakes, and continuous machine learning data pipelines.