Airlines & Aviation. Six workloads, one endpoint.
Carriers, cargo, MRO & ground handling — the workloads below need more than one data model at once, which is exactly why they stall on a stitched stack.
Full-service and low-cost carriers, cargo operators, MRO providers and ground handlers operating 50+ aircraft under thin per-seat margins.
The forcing function.
Passenger traffic keeps growing against constrained aircraft availability while yields fall. AI has moved from experiment to core infrastructure across turnarounds, disruption handling and maintenance — and integrated disruption recovery means optimising aircraft, crew, passengers and maintenance in one coherent plan. That plan is a join across four domains, and it is only possible if those domains share a store.
The recovery graph — one coherent disruption plan is a join across aircraft, crew, passengers and maintenance.
reduction in disruption recovery cost from integrated IROPS optimisation — SITA
faster aircraft reactivation and less maintenance ground time — IATA data
forecast passenger traffic growth in 2026 against constrained aircraft supply — IATA
Six workloads, five query shapes.
Almost no workload here needs only one data model — which is why single-model databases deliver it only with a second system and a sync problem.
Aircraft, crew, slots, passenger itineraries and maintenance modelled as one graph, so recovery optimises across all four constraints simultaneously rather than sequentially.
Lower recovery cost per disruption event and fewer misconnected passengers.
Sensor time-series joined with vector similarity over technical-log narratives and prior defect resolutions — find the closest historical fault, not just the threshold breach.
Reduced maintenance-driven cancellations and less unscheduled ground time.
Demand signals, competitor fares and live inventory blended with passenger embeddings to construct the offer at the moment of intent.
Ancillary revenue per passenger uplift on the same traffic base.
Bookings, tiers, service recovery history, co-brand relationships and household links in one queryable view — graph plus semantic retrieval driving proactive service.
Higher direct-booking share and better retention of high-value flyers.
Hybrid retrieval across manuals, MEL, SOPs, NOTAMs and safety reports, with sourced answers for OCC, crew and engineering — every response traceable to a document and revision.
Faster, better-evidenced operational decisions; less time lost to manual lookup.
Bookings, forwarder relationships, capacity and historical performance modelled together to optimise allotments and surface irregular booking behaviour.
Improved cargo load factor and yield; fewer no-show and abuse losses.
Impact statements are directional targets referenced to published industry research — calibrate against your own baseline.
The stack this replaces in Airlines & Aviation.
Five licences, five sync jobs, five security perimeters — collapsed into one atomic store.
One coherent recovery plan across aircraft, crew, passengers and maintenance — which is a join, and therefore a database decision.