By Airframe InsightsMay 14, 2026

The Stack Migration Report

A team receives a Splunk renewal quote and evaluates Cribl with Snowflake. In this illustrative example, observability spend falls by half within two quarters, and the SRE team's data lands in the warehouse it already pays for. We examine twelve named migration paths across 232,000+ organizations and 174,000+ deployment case studies. The diagrams show patterns and direction, not measured migration volumes.

The read

Three signals before migration.

Three signals recur before every named migration examined here. They appear in deployment narratives 18 to 36 months before the incumbent reports a quarter that confirms the change. This is an observed pattern in the corpus, not a prediction.

01The incumbent’s product stops moving.
02The challenger wins net-new projects.
03The economics invert.

Fig. 01 · Legacy stack to modern stackDirectional · patterns in the registryRibbon thickness is schematic, not a measured countIllustrative of patterns the registry surfaces

The incumbent is not losing because the insurgent is better. The incumbent is losing because the category rewrote itself around them.

Airframe Insights

Twelve named migration paths.

These twelve legacy-to-modern paths recur most often in the registry. Bars represent editorial weight in the corpus, not a measured ranking. Each reason code identifies the dominant driver we read across deployment narratives.

01Splunk→Cribl + SnowflakeBill shock, route the noise, land the rest in the warehouse already paid for

02Confluence→NotionAI-era surface, blocks model, search and assistants the writers actually use

03Jenkins→GitHub ActionsArchitect preference: configuration as code, fewer plugins, and runners where the code lives

04Legacy code editors→CursorAI-era capability gap: an editor-native agent with multi-file edits

05Teradata→SnowflakeCost compression: separate storage and compute without the former capacity ceiling

06Cloudera→DatabricksAI workload gravity: a lakehouse for ML workloads and unified governance

07Tableau / Looker→HexNotebook-native: SQL and Python together in an analyst workflow built around AI

08Siebel→SalesforceWave II displacement: multi-tenant cloud replacing the remaining on-prem CRM seats

09PeopleSoft→WorkdayConsolidation play: HCM and finance on one ledger, with mobile-first manager workflows

10Ariba→Coupa + RampContract and leverage cycle: procure-to-pay separates from card and expense controls

11Legacy enterprise search→GleanAI-era capability gap: retrieval across SaaS tools, returning answers instead of links

12Manual GTM tooling→ClayAI-era capability gap: enrichment and orchestration connected to outbound agents

Fig. 02 · Twelve named legacy-to-modern pathsBars are editorial weight, not a measured countReason codes aggregated from deployment narrativesDirectional read of patterns the registry surfaces

Why teams moved

Ten reason codes recur as primary drivers across 174,000+ deployment case studies. Bars show editorial weight, not precise percentages.

01Bill shock, cost compressionDominant

02AI-era capability gapStrong

03OSS and self-host leverageStrong

04Architect and SRE preferenceNotable

05Consolidation playNotable

06Contract and leverage cycleNotable

07Governance and data residencyEmerging

08Acquired vendor, forced moveEmerging

09Talent and hiring gravityLong tail

10Other, idiosyncraticLong tail

Fig. 03 · Reason codes the registry surfaces most oftenEditorial weight, not precise percentagesBars directional, relative to the dominant patternIllustrative of patterns the registry surfaces

Bill shock is the most prominent single driver. Together, the next three codes (AI-era capability gap, OSS leverage, and architect preference) carry substantially more editorial weight than price alone. The corpus suggests that incumbents need to respond to changes in how customers work, alongside the cost of their current software.

The corpus suggests that two migrations are accelerating into Q3 within the same engineering organizations: path 04, from legacy editors to Cursor and editor-native agents, and path 11, from legacy enterprise search to Glean and retrieval tools. Their renewal windows overlap. When both reach the CFO in one quarter, teams may review the broader workflow and open another migration path. These twelve paths provide a starting point for conversations with peers in the registry.

Registry and sources

Airframe reports editorial patterns when independent deployment artifacts repeatedly show directional movement. To discuss the underlying registry, contact hello@airframe.ai.

Organizations

232,000+ tracked in the registry

Signal base

174,000+ deployment case studies

Vendor corpus

2,398 software leaders, 1969 to 2026

Independence

Zero vendor money behind the registry. We are paid the same whichever tool the read points to.

Talk to us

Assess your software stack.

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Airframe · 2026

Coverage24,000+ products · 232,000+ organizations · 174,000+ deployment case studies.

IndependenceZero vendor funding behind the registry. We are paid the same regardless of which tool the research recommends.

Contacthello@airframe.ai