InsightEdge Smart Augmented Transactions provides you with real-time feedback on business operations, rapid innovation on insight-driven workloads, and the ability to unlock live operational intelligence across the business. The in-memory computing platform delivers the necessary components of a cloud-native translytical architecture that combines transactions and analytics workloads in a single platform to empower real-time analytics immediately over transactional data.

Smart Augmented Transactions Highlights

Forrester compare chart

Forrester Compares Translytical Platforms

Forrester named GigaSpaces a strong performer in the latest Forrester Wave™: Translytical Data Platforms. InsightEdge leads across all in-memory data grids, in-memory NoSQL and NewSQL databases.


Demo: Flight Delay Prediction

Watch this short demo to see how InsightEdge Smart Augmented Transactions can predict flight delays and pinpoint the contributing factors to the delays. See the actual demo architecture.



What Makes Smart Augmented Transactions, Smart?

Enrich Real-Time Analytics with Historical Context

Smart Augmented Transactions powers event-triggered real-time analytics on streaming data enriched with historical context to help your insight-driven organization address time-sensitive decisions – enhancing business operations, regulatory compliance and customer experience.

machine and deep learning

Out-of-the-Box Machine and Deep Learning

Contains the frameworks for scalable data-driven solutions including SQL, Spark, streaming, ML and deep learning. Your applications leverage faster and smarter insights from ML models running on any data source whether structured, unstructured or semi-structured.

enhanced sql pushdown predicates

Enhanced Pushdown Predicates

Smart Augmented Transactions enhances the Agile Spark pushdown predicate capability by leveraging our native advanced indexing mechanism, to retrieve only relevant data entries when running a query (filter). This ability to filter directly on the source (instead of on the target as is done in the vanilla Apache Spark architecture) dramatically improves performance and reduces network overhead.