Fraud Ring & Synthetic Identity Detection
Uncover circular transactions, shared device fingerprints, and hidden relationship networks in milliseconds during checkout or loan origination.
VaagaGraph
Engineered specifically for TB-scale graph topologies running inside micro-footprint 1GB Kubernetes pods. Deliver sub-10ms traversals, consistent hash sharding, zero data loss quorum WAL, and native dynamic match scoring.
<10ms
Traversal Latency
1GB
Pod Memory Footprint
50%+
Dynamic Match Scoring
Zero
Data Loss Quorum WAL
Cost Efficiency & Scale
Traditional graph databases require massive multi-terabyte RAM cloud instances that inflate infrastructure bills and crash unpredictably during heavy traversals. VaagaGraph distributes graph partitions horizontally across lightweight 1GB pods.
Run your largest graph topologies inside standard 1GB Kubernetes pods. Eliminate monolithic memory instances and scale dynamically with cluster demand.
Graph nodes and edges are partitioned across shard rings deterministically, eliminating cross-node lock contention and ensuring predictable sub-10ms traversals.
Built-in dynamic threshold queries (25%, 50%, 75%+) calculate multidimensional relationship compatibility and fuzzy pattern matches directly within the engine.
Raft-inspired quorum Write-Ahead Log guarantees that committed graph mutations survive node restarts and network partitions with strict ACID durability.
Frequently traversed relationship paths are held in high-speed local memory caches, keeping p99 traversal latencies below 5 milliseconds.
Deploy seamlessly on AWS EKS, Google GKE, Azure AKS, or air-gapped on-premise Kubernetes clusters with zero third-party telemetry or licensing lock-in.
Commercial Use Cases
Where VaagaGraph provides unmatched speed, security, and infrastructure efficiency.
Uncover circular transactions, shared device fingerprints, and hidden relationship networks in milliseconds during checkout or loan origination.
Model multi-party ownership histories, encumbrances, and transfer deeds to expose broken title chains before legal commitments are made.
Calculate mutual compatibility across millions of multi-dimensional profiles using weighted graph traversals and dynamic threshold queries.
Technical Standards
High-throughput traversals, ACID durability, and seamless horizontal autoscaling.
Talk with our distributed database architects to evaluate running your graph topology in lightweight 1GB pods.
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