Logistics & Network Optimization

Every network has a graph underneath it.

Supply chains, power grids, telecom networks, pipelines. Optimize flows, prevent failures, and make better decisions by querying the connections that matter.

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The problem

Physical networks are too interconnected to query flat.

Complex dependencies don't fit in tables

Supply chains, power grids, and telecom networks have hundreds of layers of dependency. Relational databases can't traverse those structures efficiently. Each JOIN adds latency. Each hop multiplies complexity.

Bottlenecks appear and disappear in seconds

Network conditions change constantly. Fault detection, capacity, and route optimization that run on yesterday's data arrive too late. Decisions need to be made on the live state of the network.

Failures cascade in ways that are hard to predict

One node going offline can cascade through dozens of dependent systems. Without a graph model, it's impossible to trace how a failure propagates or which components are most at risk.

Use cases

Three networks. One graph engine.

Supply chain & logistics

Optimize routes and eliminate production delays

Model suppliers, warehouses, carriers, and customers as a connected graph. Run shortest-path and flow optimization algorithms to minimize end-to-end production time and identify critical dependencies before they become bottlenecks.

Route optimization across complex multi-tier supply networks
Identify single points of failure and critical path dependencies
Real-time migration from logistics systems via Kafka or Redpanda
Investment analysis: understand which network nodes drive the most value

Energy & power grids

Detect faults and prevent unexpected failures

Map power grids, gas pipelines, and energy networks as graphs. Analyze capacity, detect network issues before they escalate, and give engineers a complete visual picture of the system with real-time latency.

Deep connection traversal across grid components in milliseconds
Fault detection and capacity analysis on live grid data
Visual representation for identifying bottlenecks and weak spots
Graph algorithms to highlight high-risk nodes and weak links

Telecom & IT networks

Analyze topology and trace propagation paths

Model network infrastructure as a graph to find bottlenecks, trace how changes propagate, and run network analysis at scale. Improve engineer productivity with a high-performance tool purpose-built for network analytics.

Real-time topology mapping for large-scale networks
Propagation analysis: how does a change cascade through the system?
Centrality and community detection to find critical infrastructure
Dynamic algorithmic updates incrementally as network state changes

Customer storyHow Volue Optimized Power Grid Management with Memgraph

Check out how Volue uses Memgraph for real-time power grid optimization without the infrastructure bloat.Read story

Capabilities

Why Memgraph.

Capabilities that make these use cases production-ready.

Graph algorithms
Shortest path, betweenness centrality, community detection, PageRank: all callable as Cypher procedures on live network data. Dynamic algorithms update incrementally as the network changes, no full recomputation required.
Real-time ingestion
Connect directly to Kafka, Pulsar, or Redpanda for continuous ingestion. Network state is always current. No batch windows, no stale topology. Concurrent writes without degradation.
Visualization
See the full network, not just the data. Memgraph Lab provides a visual interface for exploring graph topology, identifying bottlenecks, and tracing propagation paths. Engineers get a complete picture of the network they're managing.

Resources