GigaSpaces Optimizes the Balance Between Performance and Cost with Enhanced InsightEdge Portfolio

GigaSpaces, a provider of in-memory computing platforms that drive digital transformation, has enhanced its InsightEdge Portfolio, offering advanced functionality to reduce memory footprint for optimizing infrastructure costs, boost SQL query and BI performance, and increase an organization’s agility with cloud-native lifecycle management.

“As our customers accelerate their digital transformation and cloud migration initiatives, following the COVID-19 disruption, the sensitivity to cloud expenses and elasticity, along with the need for high performance and speed is growing more than ever,” said Yuval Dror, VP R&D at GigaSpaces. “The release of InsightEdge Portfolio version 15.8 delivers our best performance results to date for operational and analytical workloads, and higher elasticity to handle expected and unexpected peaks; all while reducing infrastructure and cloud costs.”  

This new release improves the balance between performance and cost and enhances an organization's ability to deploy and manage new services with the following benefits for all InsightEdge portfolio platforms including Smart Cache, Smart ODS and Smart Augmented Transactions:

  • Smart RAM footprint reduction: In-memory data store RAM is optimized to reduce infrastructure costs by up to 70% while retaining blazing performance.  Using the GigaSpaces Ops Manager, an object’s RAM storage footprint can be automatically reduced. This substantially lowers costs—for both spending per TB on the cloud and on-premise hardware, along with added savings for replicated clusters located in different regions or data centers. 
  • Smart data locality to boost SQL query performance: 10x faster response time is achieved for queries, reporting and BI by automatically replicating selected small tables of data to the nodes in the cluster to accelerate server-side JOIN performance. The new Broadcast Objects feature replicates smaller static tables that are used frequently when combining rows from two or more tables, for example daily exchange rates. With a minimal impact on RAM footprint, a significant boost in response time and higher concurrency are achieved.  
  • Cloud-native lifecycle management: The latest support of Kubernetes Operator allows organizations to use both the Kubernetes Helm for day-1 deployment in a cluster and also the day-2 operations of managing application workloads and auto-scaling up or out to support unexpected workloads. 

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