Analytics
Geode provides enterprise-grade analytics capabilities designed for both batch and real-time graph analysis. Leverage advanced graph algorithms, streaming pattern detection, and machine learning-powered insights to extract value from your connected data.
Overview
The analytics subsystem in Geode combines traditional graph algorithms with modern streaming analytics and machine learning techniques. Whether you need to analyze social networks, detect fraud patterns, or identify anomalies in real-time data streams, Geode’s analytics engine delivers high-performance results with minimal latency.
Built on top of Geode’s storage engine, analytics operations benefit from memory-mapped I/O, optimized index structures, and parallel execution capabilities. Real-time analytics leverage Geode’s Change Data Capture (CDC) integration and backpressure handling to process streaming data at scale.
Key Features
- Graph Algorithms: PageRank, community detection, shortest paths, centrality measures, and more
- Real-time Pattern Detection: Streaming analytics with sub-second latency for time-sensitive insights
- Anomaly Detection: ML-powered anomaly detection for fraud, security, and quality monitoring
- CDC Integration: Change Data Capture for continuous analytics on live data streams
- Scalable Execution: Distributed algorithm execution across federated deployments
Topics in This Section
- Graph Algorithms - Complete reference for supported graph algorithms including PageRank, community detection, shortest paths, and centrality measures
- Real-time Analytics - Streaming pattern detection, anomaly detection with ML, CDC integration, and backpressure handling
Learn More
- Real-Time Analytics - Streaming pattern detection, anomaly detection with ML, CDC integration
- Query Performance Tuning - Optimize analytics queries for maximum throughput
- Materialized Views - Cache analytics results for fast repeated access
- Architecture: Analytics - Technical architecture of the analytics subsystem