Real-Time Streaming
Data Processing
A high-performance streaming engine that ingests, transforms, enriches, and routes data in real time — before it is stored, searched, or analyzed.
Built for Streaming at Scale
ShyftStreamz processes data as it flows — enabling filtering, enrichment, normalization, and routing without introducing storage or query latency.
Universal Ingest
Agents, syslog, files, queues, and cloud services feed a unified pipeline model.
Inline Processing
Filter, route, enrich, mask, dissect, and normalize events in real time.
Stream Intelligence
Apply detection, aggregation, and transformation before data reaches storage.
Flexible Routing
Route to ShyftStore, ShyftSearch, and external systems simultaneously.
Data Protection
Mask sensitive fields and enforce compliance controls within the stream.
Backpressure-Aware
Built-in flow control helps prevent data loss during downstream slowdowns.
Highlights
Real ShyftStreamz pipelines running live — capability highlights across the full platform.
How ShyftStreamz Works
A streaming architecture designed for continuous flow, transformation, and delivery.
Ingest
Events enter from agents, network sources, cloud services, or applications.
Process
Data is filtered, enriched, normalized, and evaluated in real time.
Route
Processed data is routed to one or more destinations based on content or policy.
Deliver
Events delivered reliably to ShyftStore, ShyftSearch, or external systems.
Central to the Platform
ShyftStreamz connects ingestion, storage, and search through real-time processing.
📦 ShyftStore
Processed data is delivered for lifecycle-aware storage and retention.
🔍 ShyftSearch
Enriched events are immediately available for search, analytics, and detection.
🧩 Modular Pipelines
Pipelines can be reused and evolved independently without disrupting data flow.
⚙️ Independent Scaling
Scale streaming separately from storage and search as data rates grow.
Process Data While It Moves
Apply intelligence, control, and structure to your data before it is stored or searched.