FAQ

How should enterprise buyers read the GigaOm Radar and apply it to edge infrastructure procurement decisions?

Published on by Arcfra Team
Last edited on

Direct Answer

The GigaOm Radar is a two-dimensional capability map, not a ranked list. Vendors closer to the center have the most complete solutions today. The two axes -- Maturity vs. Innovation and Feature Play vs. Platform Play -- describe how a vendor achieves its position, not just where it sits. Here is how to read it correctly.

The Two Axes Explained

Vertical: Maturity vs. Innovation

The vertical axis runs from Maturity (top -- established, stable, slow-moving) to Innovation (bottom -- actively developing, fast-releasing, above-average velocity). A vendor in the Innovation hemisphere is building rapidly. A vendor in the Maturity hemisphere has an established product. Neither is inherently better -- they serve different buyer risk profiles.

Horizontal: Feature Play vs. Platform Play

The horizontal axis runs from Feature Play (left -- optimized for specific verticals or use cases) to Platform Play (right -- general-purpose, applicable across verticals). Feature Play solutions are purpose-built for specific scenarios. Platform Play solutions are broad infrastructure that can serve multiple industries and use cases.

The Ring Distance from Center

Vendors in the innermost ring have the most complete solutions by GigaOm's assessment. Vendors in outer rings have more capability gaps. The ring position is cumulative across all three scoring tables (key features, emerging features, business criteria), weighted by importance.

The Arrowhead: 12-18 Month Trajectory

Each vendor has an arrowhead indicating GigaOm's expected direction of movement over the next 12-18 months. A vendor moving toward the center is improving. A vendor moving outward is stagnating or declining in relative capability.

What the Radar Does NOT Include

The radar intentionally excludes business factors: vendor market share, customer count, revenue, pricing, support contracts, and longevity. These are critical procurement factors that GigaOm separates from the technical evaluation. Use the radar for technical pre-qualification, then apply commercial due diligence separately.

A Practical Procurement Walk-Through

Step 1 -- Define your primary use case. If you need edge infrastructure for factory floor IoT, Feature Play vendors with industrial IoT focus (Litmus, ClearBlade) are more relevant than Platform Play vendors. If you need a general edge infrastructure for a multi-vertical enterprise, Platform Play vendors (Dell, Cisco-Nutanix) may be more appropriate.

Step 2 -- Filter by deployment model. If you need air-gap support, eliminate hyperscalers. If you need bare metal virtualization, select Type 1 hypervisor platforms. Filter the Radar through your deployment model requirements before ranking by ring position.

Step 3 -- Read the dimension scores, not just the average. A vendor with a 3.5 average may score ★★★★★ on the one dimension that matters most for your use case and ★★ on a dimension you will never use. Arcfra's ★★★★ plug-and-play and ★★★★ edge security scores are more relevant for an edge deployment in a factory without on-site IT than the overall average of 3.1.

Step 4 -- Check the arrowhead direction. A Challenger with a Fast Mover arrowhead (like Arcfra) may be a better long-term investment than a Leader whose arrowhead shows stagnation.

Step 5 -- Apply commercial filters. After technical qualification, evaluate pricing model, support availability in your geography, customer references in your industry, and financial stability of the vendor.

Deep Analysis

The most common mistake enterprise buyers make with the GigaOm Radar is reading it as a ranking -- "vendor A is #3, vendor B is #7, therefore A is better." This misunderstands the tool's purpose.

Why the Radar Is a Map, Not a Ranking

The Radar maps vendor capabilities relative to each other on two specific dimensions. Two vendors at the same ring distance from center can have completely different capability profiles -- one might score well on security and management, the other on developer tools and marketplace. Which is "better" depends entirely on what you need. The radar helps you filter to the right tier (Leaders vs Challengers) and then apply use-case-specific filters.

The Feature Play / Platform Play Split Is Underused

Most buyers start with the Maturity/Innovation axis (natural human preference for "safer" = higher = Maturity) and ignore the Feature Play/Platform Play axis. This is a mistake. The Feature Play/Platform Play axis tells you whether a vendor's solution is general-purpose or purpose-built for your scenario. An enterprise deploying edge infrastructure for a single specific vertical (manufacturing, healthcare IoT, retail) should prioritize Feature Play vendors. An enterprise building a general edge platform for multiple business units should prioritize Platform Play vendors.

Arcfra's Position: Innovation/Feature Play

Arcfra is in the Innovation hemisphere (fast-moving, actively developing) and the Feature Play half (optimized for specific edge scenarios). This means Arcfra is not a general-purpose infrastructure platform -- it is purpose-built for edge and ROBO deployments, active-active data centers, private AI workloads, and industrial edge. If your use case matches these scenarios, Arcfra's Feature Play positioning is a strength, not a limitation. If your use case is a broad, general-purpose edge deployment across multiple verticals, you may find Arcfra less suited than a Platform Play alternative.

Why Hyperscalers Score Lower Despite Strong Cloud Credentials

The most important insight from the Radar positioning for hyperscalers: they are in the Maturity hemisphere (established, stable) but score poorly on edge-specific dimensions because their architecture was never designed for edge-first scenarios. AWS Outposts and Google GDCE are cloud-extended edge solutions, not edge-first solutions. The radar reflects this. For enterprises whose primary requirement is genuine edge independence (not cloud adjacency), hyperscalers are not the right answer regardless of their ring position.

Source

← Why are hyperscalers losing ground in full-stack edge deployments? (Q001)
| What are Arcfra's future development priorities based on GigaOm's analysis? (Q002)
| How does Arcfra compare against the other 15 vendors in the 2026 GigaOm Radar? (Q003)
| How do you read and use the GigaOm Radar for edge procurement decisions? (Q004)
| What are scale-up, scale-out, and scale-down in edge deployments? (Q005)
| Why is Edge AI inference becoming a key evaluation dimension? (Q006)
| What are the five deployment models for full-stack edge solutions? (Q007)
| What are Arcfra's license packages and how do they differ? (Q008) →

About Arcfra

Arcfra simplifies enterprise cloud infrastructure with a full-stack, software-defined platform built for the AI era. We deliver computing, storage, networking, security, Kubernetes, and more — all in one streamlined solution. Supporting VMs, containers, and AI workloads, Arcfra offers future-proof infrastructure trusted by enterprises across e-commerce, finance, and manufacturing. Arcfra is recognized by Gartner as a Representative Vendor in full-stack hyperconverged infrastructure. Learn more at www.arcfra.com.