echoloc
Echoloc Research·Report 03·July 2026

The Displacement Index

Every quarter, thousands of job postings quietly announce which technologies companies are walking away from. We read 4.7 million active postings, verified the direction of every signal against raw text, and ranked the 19 technologies enterprises are actively ripping out right now — and where they're going instead.

Every row on the board is measured from live job postings: N companies currently hiring to leave that technology, destination = what the same companies adopt. The board is the dataset.
479
companies actively leaving one of the 19 indexed technologies
1 in 1,000
postings is now a rip-and-replace req — an all-time high in our data
84%
of exit signals from postings published in the last 90 days
1,476
companies show a replacement signal of any kind

Vendors publish adoption numbers. Nobody publishes churn. But when a company hires an engineer to "migrate our analytics stack from Power BI to a GCP-based platform", the churn is right there in the posting — funded, dated, public. We read 4.7 million active postings and pulled out every explicit exit.

One thing makes this index different from a survey: we verified the direction of every signal against raw posting text, technology by technology. Extractors love to confuse "migrating to X" with "replacing X" — so seven technologies that looked like they belonged here were thrown out (the full casualty list is in the methodology). What's left are 19 technologies with clean, explicit exit language and 479 companies actively hiring their way off them.

Finding 01

Displacement is accelerating — 1 in 1,000 postings is now an exit req

The replacement signal is the rarest and most valuable thing we extract: a posting that names the technology being killed. Its share of all hiring has climbed all year and hit 100 per 100K postings in June — the highest we've measured. 84% of the signals behind this report are less than 90 days old.

Rip-and-replace hiring just hit an all-time high
Postings carrying an explicit replacement signal, per 100,000 postings published each month.
Replacement postings per 100K
255075100 100 Sep 25Feb 26Jun 26

June 2026: exactly 1 in 1,000 new job postings describes ripping a technology out — up ~40% from autumn 2025. Displacement is accelerating even where individual migrations (like SAP's) have plateaued: the churn is spreading across more categories at once.

Shares, not raw counts — index volume grew unevenly. Months before continuous indexing (Jan 2026) enter via still-open postings and skew to long-lived roles.
Finding 02

Who's leaving what: banks quit SAS, SMBs outgrow QuickBooks, everyone modernizes .NET

The index has personalities. SAS is a banking exodus: Citi · PNC · Danske Bank · Banque de France are all hiring to move statistical workloads to Python and Databricks — 12 of its 21 leavers are 1,000+ companies. QuickBooks is the opposite: 24 of 25 leavers are under 1,000 employees — it's not churn, it's graduation, mostly toward NetSuite.

Jenkins is quietly bleeding enterprises (State Farm · ABN AMRO · Suncorp Group), VMware's post-acquisition exodus is real (Ericsson · Dassault Systèmes · NetApp — toward Kubernetes and Nutanix), and even Salesforce shows 32 companies heading for the door, including Booking.com · Veeva Systems · UiPath — with no consensus destination, which is its own story. Oracle's 56 leavers include Siemens · RBC · Salesforce. And Microsoft Access refuses to die quietly: Metropolitan Transportation Authority is still hiring people to finally kill it.

The Displacement Index, in full
Companies with an active, direction-verified exit signal per technology. "Enterprise" = share of leavers with 1,000+ employees. Destination = most common co-adopted successor (shown when ≥3 companies share it).
LeavingCategoryCompaniesEnterpriseCommon destination
SAP ECCERP8164%SAP S/4HANA
SQL ServerDatabases6038%Databricks / Fabric
OracleDatabases5650%AWS / PostgreSQL
SalesforceCRM3234%
VMwareInfrastructure2544%Kubernetes / Nutanix
QuickBooksERP254%NetSuite / Brex
AngularFrameworks2335%React
SASAnalytics2157%Python / Databricks
SAP R/3ERP2152%SAP S/4HANA
.NET FrameworkFrameworks2035%.NET (modern)
.NETFrameworks2035%
JavaLanguages2035%
JenkinsDevOps1856%GitLab / Terraform
Microsoft AccessDatabases1747%
TableauAnalytics1638%
InformaticaAnalytics1567%Power BI / Databricks
Dynamics NAVERP157%
PHPLanguages1429%
AS/400Legacy platforms1338%
Vendor self-rows (a vendor "replacing" its own product) and consulting/staffing firms excluded. Every count is companies, not postings.
Finding 03

Where they're going: cloud-native catches the refugees, AI rides along

Displacement money doesn't disappear, it lands somewhere. Among companies actively leaving an indexed technology, the most-adopted destinations are Kubernetes, the hyperscalers, Databricks and Python — the standard modernization playbook. The surprise is what's riding along: RAG (14 companies), LangChain (12) and Cursor (10) all rank among the top technologies leavers adopt. Companies don't just swap old for new — the replatform budget doubles as the AI budget.

Where the leavers land
Technologies most adopted by the 479 companies mid-displacement (excluding same-vendor upgrades like ECC → S/4HANA).
Infrastructure & dataAI build stack
Kubernetes
19
AWS
17
RAG
14
Databricks
14
Python
13
Power BI
12
GCP
12
LangChain
12
Terraform
12
Cursor
10
Microsoft Fabric
9
React
9
Cloud-native infrastructure catches most of the exits — and the AI build stack rides along: RAG, LangChain and Cursor all rank among the top destinations. A rip-and-replace program is an AI-adoption moment.
What we refused to count
Technologies with raw replacement signals that failed direction verification — and why.
TechnologyRaw signalsWhy it's out
SAP S/4HANA58direction inversion: postings describe migrations TO S/4HANA (1 away-signal vs 42 toward in raw text)
Dynamics 36513direction inversion: destination of NAV/AX migrations
PostgreSQL17direction inversion: mostly the destination of Oracle exits
Snowflake18contaminated: vendor pitch postings and migrations TO Snowflake
AWS / Azure64on-prem-to-cloud postings mislabel the destination; real cloud-to-cloud churn kept separately below
SAP (generic)40ambiguous: overlaps ECC/R/3 rows and vendor-neutral consulting language
SSIS12implied-deprecation language only; no explicit replacement statements in sampled postings
This is the part most "churn reports" skip. An extractor that can't tell "migrating to X" from "replacing X" will happily rank X as dying while it's winning.
The data behind this report

Every row of this index is a company list

The free CSV has the 50 largest companies with a verified exit signal — who they are, what they're leaving, what they're adopting, plus hiring context. Each individual row of the index ("companies leaving VMware", "companies leaving SAS"…) is available as a full list with quarterly refresh — that's the product. Custom pull against your account list is free.

Methodology

How this was measured

Echoloc continuously indexes public job postings; at analysis time: 15,207,852 postings, 4,747,583 active, across 761,828 companies. An LLM pipeline extracts technologies with context (using / adopting / evaluating / replacing). Replacement signals aggregate to company level from active postings only.

  • Direction verification: for every candidate technology we ran a lexical screen of raw posting text ("migrating from X", "off X", "replace X" vs "to X") plus manual reading of sampled postings. Seven technologies failed and were excluded — see the table above. This matters: naive extraction ranks S/4HANA as the #3 "dying" technology when it is in fact the #1 destination.
  • Excluded from all counts: consulting, IT-services, staffing and outsourcing industries (10 categories), named professional-services firms, and vendor self-rows (a vendor "replacing" its own product).
  • Destination pairs are co-occurrence: the same company shows an exit signal for X and an adoption signal for Y. Shown only at ≥3 companies. Absence of a destination means no consensus, not no movement.
  • Momentum uses shares of postings per month; months before continuous indexing (Jan 2026) are survivorship-biased toward long-lived postings.
  • Counts are companies, not postings, and are conservative: a company migrating without public hiring is invisible to us.

Questions, or a number you'd like re-cut? [email protected].

Cite as: Echoloc Research, "The Displacement Index", July 2026. https://echoloc.ai/research/displacement-index-2026/ — data from 4,747,583 active job postings, pulled 2026-07-20.