Distributed Computing Scalable Architecture with GigaSpaces Elastic
Open Interfacing Layer
Supports multiple languages and frameworks
Achieve easy migration, reduced learning curves, and faster time to market by leveraging existing skillsets such as Spring, Java, JPA, .Net, and C++.
Virtualized Deployment Infrastructure
Any environment, anytime, anywhere – traditional data center, public/private cloud, or hybrid
Isolate the runtime environment, physical address, and platform type from your data grid. The system takes care of provisioning your data grid instances onto the best available resources, and self-adjusts to maintain utilization levels as machine availability changes over time.
In-Memory Data Grid
Provides high performance, dynamic linear scalability, and always-on availability
- Query Processor: Enables applications to query data using simple as well as complex SQL-like queries.
- Memory Manager: Sets upper limits on memory usage in your cluster nodes, with automatic handling of overflow
Cluster & Replication Layer:
- Flexible topologies enable you to arrange distributed cache in partitions, replicated units, or a combination of both.
- Data can be replicated over geographically distributed deployments.
- Entire cluster can be transparently accessed from any machine.
Discovery & Communication
- Enables cluster members to automatically discover other members; unicast and multicast discovery support.
The GigaSpaces In-Memory Data Grid (IMGD) supports the follwing deployment topologies:
All the topologies support co-locating business logic with any of the IMDG instances, enabling fast data processing and eliminating serialization and network overhead once data is accessed.
- Fully replicated: Each member contains all of the data. Replication between nodes is done synchronously or asynchronously
- Partitioned: Each node contains a different subset of the data
- Partitioned: Each node contains a different subset of the data.Regardless of the IMDG cluster deployment topology, a client can run a near-cache (called local cache/view).
Side Cache with Local Caching
System of Records (SoR) with Write Behind
System of Records (SoR) with Local Caching