Use Case
Decide Before the Moment Passes
A decision made after the transaction closes is just a report. MariaDB GridGain runs your rules and models on live events, so the answer arrives while it can still change the outcome.
What is real-time decisioning?
Real-time decisioning executes business rules, analytics and ML models against live event streams, delivering answers within the transaction window. MariaDB GridGain unifies the digital integration hub, event processing and compute in one platform, so decisions happen where the data resides.
Capabilities
Real-time decisioning needs
A decision is only as good as the data behind it. MariaDB GridGain acts as a digital integration hub, bringing every relevant source into memory and running the logic there.
Stream processing on arrival
Events from Kafka and other sources are processed as they land, with continuous queries firing logic as the data changes rather than on a schedule.
Colocated rules and models
Business rules, scoring and machine learning models execute on the nodes holding the data, eliminating network round trips to a separate engine.
Live and historical context together
Balances, limits, entitlements and past behavior sit in memory alongside the event, allowing each card swipe to be judged against recent activity.
Decisioning through demand spikes
Process millions of events per second across a shared-nothing cluster, keeping decisions within the required time window during Black Friday, market swings or outages.
Feature preparation in place
Events are enriched with context, features extracted and embeddings generated on the same cluster, eliminating the need to write data out and read it back before scoring.
Real-time decisioning relies on the same underlying infrastructure but takes different forms across industries
These four patterns cover most customer scenarios.
Fraud and risk in the authorization window
Score transactions against behavioral history and rules before approval, rather than finding the loss in tomorrow’s batch.
Dynamic pricing and quoting
Calculate prices using volume, inventory, promotions and competitive signals, reducing response times from seconds to milliseconds.
Next-best action and personalization
Select offers, upsells or content at the moment of interaction, using current behavior and entitlements rather than overnight updates.
Dispatch and disruption response
Re-plan routes, crews, fleets and schedules as conditions change, running models against live telemetry to avoid hazards and keep operations moving.
Recommended resources
Get started
Start building with MariaDB
One real-time database platform you can trust, for everything you run today and everything you build next.
Frequently asked questions
Real-time decisioning runs business rules, analytics and machine learning models against live event streams, making decisions while the transaction is still open rather than reporting outcomes afterwards.
Real-time analytics typically means fresh dashboards and queries. Decisioning determines how the system acts: approving, pricing, routing or recommending within the transaction, without a human needing to read a chart first.
MariaDB GridGain keeps the historical context a decision needs in memory alongside live events to support real-time decisions. MariaDB Exa analyzes trends and large data volumes rather than individual events.
Yes. Models execute on the cluster nodes holding the data, so feature lookup and scoring complete without a network hop to a separate serving layer. Execution typically takes tens of milliseconds.
Events stream through Kafka, operational databases, mainframe systems and APIs. As a digital integration hub, MariaDB GridGain consolidates them into one in-memory layer so the model sees every relevant signal.
Financial services and payments for fraud and risk detection, retail for pricing and personalization, telecommunications for offers and subscriber actions, and transportation for dispatch and disruption response.