Kubernetes vs Nomad vs Expanso – Choose the Right Orchestrator

Kubernetes vs Nomad vs Expanso: Which Orchestrator is Right for Your Data?

If you are an engineer trying to manage petabytes of data scattered across sources, you know the pain of dragging it all to a central cluster. It takes days—if not weeks—and costs a fortune in bandwidth. Traditional orchestrators like Kubernetes and Nomad assume you will move data to compute. But data gravity, sovereignty, and edge scale make that slow, costly, and risky.

Instead of moving data to compute, Expanso brings compute to the data—whether it’s on edge devices, in the cloud, or in your own servers. The result: faster processing, lower costs, and improved security.

This guide covers:

• What Kubernetes, Nomad, and Expanso are
• The key differences among them
• When to choose each
• Why Expanso might be the missing piece in your infrastructure

Kubernetes, Nomad, Expanso: Core Concepts and Goals

Kubernetes

Kubernetes is the industry-standard container orchestrator, offered as a hosted platform by major clouds. It shines with rich ecosystems like Helm, Istio, and Prometheus, and is built for microservices that mesh internally.

Nomad

Nomad is lightweight and flexible. It runs containers, VMs, and standalone binaries. Because it lacks an internal service mesh, it needs fewer supporting services, which simplifies setup across AWS, GCP, Azure, and on-prem.

Expanso

Expanso operates as an upstream data control plane with lightweight execution agents that run compute where data is generated or stored. It executes containers, WASM, and native binaries, and supports hardware acceleration including GPUs and specialised edge hardware. Execution is policy-driven and tightly coupled with data locality, governance, and routing.

Comparing Kubernetes, Nomad, and Expanso: Key Differences

Execution Environments

• Kubernetes: Remains focused on container orchestration, optimised for Docker and OCI workloads, with emerging WASM support that still requires additional operators and tooling.
• Nomad: Offers broader native runtime support, orchestrating containers, VMs, binaries, and JVM workloads under a single scheduler, making it attractive for mixed legacy and modern environments.
• Expanso: Operates as an upstream data control plane with lightweight execution agents that run compute where data is generated or stored. It executes containers, WASM, and native binaries, and supports hardware acceleration including GPUs and specialised edge hardware. Execution is policy-driven and tightly coupled with data locality, governance, and routing.

Lightweight Execution and Mixed Architectures

• Kubernetes: Introduces significant control plane complexity, with resource overhead that makes it less suitable for constrained edge or highly distributed environments.
• Nomad: Runs as a single binary and is lightweight, supporting heterogeneous clusters through constraints.
• Expanso: Agents are designed for deployment across cloud, on-prem, and edge environments, including low-bandwidth and intermittently connected sites. Mixed CPU architectures and hardware profiles are handled natively through scheduling policies and node capabilities.

Job Types

• Kubernetes: Manages long-running services and batch jobs but relies on external data frameworks for distributed data processing.
• Nomad: Supports service, batch, and system job types.
• Expanso: Supports batch, service, streaming, ops, and daemon-style execution models. Jobs are optimised for data pipelines, telemetry processing, AI inference, policy enforcement, and real-time filtering at scale.

Queued Execution

• Kubernetes and Nomad: Provide queueing via their schedulers.
• Expanso: Provides explicit policy-based queuing with priority classes, backoff strategies, and locality-aware scheduling so critical data is always processed first, even during reconnection storms.

Disconnected Execution

• Kubernetes: Not designed for unreliable networks and requires external systems for edge operation.
• Nomad: Supports limited edge use with a centralised control model.
• Expanso: Built for disconnected and degraded networks. Agents continue executing policies locally, buffer data, prioritise critical signals, and synchronise automatically when connectivity returns.

Security

• Kubernetes and Nomad: Centralise job metadata and often require broad data access.
• Expanso: Enforces Zero Data Access by default. Policies such as PII masking, schema enforcement, data residency, and encryption are applied at the source before data moves. Metadata and control are decentralised, dramatically reducing breach surface and compliance risk.

Quick Comparison

Choosing Your Orchestrator: Kubernetes vs Nomad vs Expanso

When to Choose Kubernetes

Best for large-scale microservices platforms with heavy networking, service discovery, and cloud-native operational requirements.

When to Choose Nomad

Strong fit for simpler orchestration with mixed runtime requirements inside a single zone or organisation.

When to Choose Expanso

Choose Expanso when data gravity, cost, compliance, and edge reliability are your primary constraints. Example: an energy company processing telemetry from thousands of wind turbines over unreliable networks applies Expanso policies at each site to filter noise, mask PII, prioritise fault signals, and ship only governed data upstream.

Conclusion

There’s no single “best” orchestrator—only the best fit for your workload. Kubernetes dominates cloud-native microservices. Nomad offers a lean, flexible scheduler for mixed workloads without heavy control planes. Expanso excels when data movement is the bottleneck, embracing Compute Over Data to cut cost, latency, and risk while enabling WASM sandboxing and hardware-aware execution.

What’s Next?

You can deploy Expanso across cloud, on-prem, and edge environments in minutes, or start immediately with Expanso Cloud.