Query / search · two names · 2026

MongoDB maps 24 current query / search seats against Elastic 31.
Query Optimization and Core Search seats at two database names

As of August 26, 2026, 6:27 a.m. PT (8/26), MongoDB maps 24 current query / search seats against Elastic 31, with 22 open jobs on that slice.

Report date 2026-08-26 Published by Metix AI Coverage 2 database names · 55 mapped current · 22 mapped open jobs
Query Bench

01MongoDB's query bench is 24 current Query Optimization / Query Execution seats

As of August 26, 2026, 6:27 a.m. PT (8/26), MongoDB maps 24 current query / search seats against Elastic 31, with 22 open jobs on that slice.

24
MongoDB current
Query Optimization / Query Execution
31
Elastic current
same function slice
55
headline current
two database names only
22
headline open jobs
MongoDB 16, Elastic 6
24 is MongoDB's query bench

MongoDB maps 24 current query / search seats. This page reads the function seat at two database names.

31 completes headline current 55

Elastic maps 31 current. The two add 24 + 31 = 55.

Most of the 22 jobs sit at MongoDB

Headline open jobs are 22. MongoDB maps 16 jobs; Elastic maps 6. This is a talent-flow contrast.

The US floor and the job book sit later

New York 7, United States 22 of 24, and jobs 16 versus 6 sit in later sections. The first screen cites 24 versus 31.

About this report.This page reads the query / search seat at MongoDB and Elastic. The mapped list can be requested through the list form.
MongoDB 24 mapped current versus Elastic 31
One mix bar: MongoDB 24 current versus 16 jobs. Segment width = that end / 40. Source: Metix AI.
Foundations Seat

02Elastic's 31 current seats are Core Search / Search Foundations, not a security-ops seat

Elastic maps 31 current query / search seats. The people side is Core Search and Search Foundations, not regional sales or consulting architecture.

Search Architect
31mapped current · Core Search layer
Search Foundations
31same bench · PM sample
Core Search
6mapped open jobs · same seat
Three cells are the seat family, not a title-count split. Current samples: Search Architect / Product Manager Search Foundations / Software Developer - Core Search. Source: Metix AI.
How to read this.31 is the thicker current search bench. The 6-job book is thinner. Regional-sales and consulting-architect titles are not the hook on this page.
US Floor vs Spread

03MongoDB is 22 of 24 US, with New York 7; Elastic is 12 of 31 US

22 of 24 MongoDB current seats are in the United States. Elastic's 31 current seats are spread, with 12 in the United States.

New York
7MongoDB · thickest city
Raleigh
2Elastic · named city
Sydney
2Elastic · named city
Toronto
2Elastic · named city
Top bar: United States 22 of 24. Middle bar: United States 12 of 31. Named remaining countries: Canada 3, Spain 3, Australia 2, Germany 2, Netherlands 2, United Kingdom 2, France 1, Greece 1, Israel 1, not a full cover of current 31. Source: Metix AI.
Thicker Query Book

04MongoDB maps 16 query jobs against Elastic's 6 search jobs

The current bench is thicker at Elastic; the job book is thicker at MongoDB: 16 versus 6.

MongoDB
16mapped open jobs · query seat
vs
5US jobs
Elastic
6mapped open jobs · search seat
vs
3US jobs
MongoDB jobs 16: United States 5, Canada 8, Ireland 3. Elastic jobs 6: United States 3, India 2, Brazil 1. Source: Metix AI.
Company Mapped current Mapped open jobs Read
MongoDB2416headline · thicker job book
Elastic316headline · thicker current bench
Headline sum5522these two database names only
This table is the citeable source. Only MongoDB and Elastic are added. This is a talent-flow contrast.
How to read this.Elastic 31 versus 6 is a thick bench, thinner book. MongoDB 24 versus 16 is the thinner bench, thicker book. This is a talent-flow contrast.
Methodology

05Why 55 / 22 is a query / search title slice, not Atlas Search product, not Glean, not Datadog APM

Function slice

Title tokens: query or search. Seat-family samples (no names published): MongoDB current Lead Engineer, Query / Query Optimization Lead / Product Manager, Query; jobs Staff Engineer, Query Optimization / Senior Staff Product Manager, Query / Senior Software Engineer, Query Execution. Elastic current Search Architect / Product Manager Search Foundations / Software Developer - Core Search. Atlas Search and ES|QL were not used as sole IN tokens. SIEM, XDR, threat, cyber, Glean, APM, observability, GTM, and sales were not used. Company-wide MongoDB or Elastic was not used.

Current and open jobs

The figures are profiles Metix maps as currently employed at that company name, and visible open jobs mapped to that name, not official headcount.

Names

MongoDB is the mongodb.com New York company record (10818204). Counts are id-only on that record; listed-name totals are not published as headcount. A bare MongoDB name collides. Elastic is elastic.co, San Francisco (6183507), id-only. A bare Elastic name collides.

As-of and source

As of August 26, 2026, 6:27 a.m. PT (8/26). Source: Metix AI. This page does not invent company-wide totals. This page sits in the series.

Limits.These figures are visible floors. 55 and 22 add MongoDB and Elastic only. The full mapped list is a separate request; this page shows no personal information.
FAQ

Questions this report answers

What is the MongoDB 24-versus-Elastic 31 query / search seat?
As of August 26, 2026, 6:27 a.m. PT, MongoDB maps 24 current query / search seats against Elastic 31, with 22 open jobs on that slice. These are Metix-mapped function-slice counts, not official headcount. Source: Metix AI.
What does 55 current / 22 open jobs add?
55 current / 22 jobs adds MongoDB 24 / 16 and Elastic 31 / 6 only. The slice is query or search as title tokens: query execution, search engineer, search relevance, query optimizer, query engine. Atlas Search and ES|QL were not used as sole IN tokens. SIEM, XDR, threat, cyber, security unless clearly a query or search engine, Glean, APM, observability, GTM, and sales are out. Company-wide MongoDB or Elastic is out. This is not a remake of a product-name cut.
Why is MongoDB 22 of 24 US while Elastic is 12 of 31 US?
MongoDB mapped current: 22 of 24 US, Germany 1, Ireland 1. Named city: New York 7; the rest of the city layer is thin. Jobs 16: United States 5, Canada 8, Ireland 3. Elastic mapped current: 12 of 31 US, Canada 3, Spain 3, Australia 2, Germany 2, Netherlands 2, United Kingdom 2, France 1, Greece 1, Israel 1. Named cities are thin: Raleigh 2, Sydney 2, Toronto 2. Jobs 6: United States 3, India 2, Brazil 1. Official hiring pages: MongoDB https://www.mongodb.com/company/careers and https://job-boards.greenhouse.io/mongodb , Elastic https://www.elastic.co/careers and https://jobs.elastic.co/.
How should the MongoDB 24 query / search map be cited?
Metix AI Talent Intelligence, 2026-08-26. Query / Search Talent Map 2026 | Metix AI. https://metix.ai/reports/series/mongodb-elastic-query-search-2026

Request the mapped list of the 55 query / search seats at these two database names

The same methodology can export mapped current profiles and mapped open jobs on the query / search seat at MongoDB and Elastic, or rerun a custom map on your target companies. The list form is the primary path.

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Aggregate report · no personal information shown · provided by Metix AI
Methodology: headline names are MongoDB and Elastic. The function slice is query / search title tokens, not Atlas Search product, not Glean, and not Datadog APM, and not company-wide MongoDB. Figures are Metix-mapped current profiles and mapped open jobs, not official headcount. As of August 26, 2026, 6:27 a.m. PT (8/26). Source: Metix AI.
Metix AI | Query / Search Talent Map 2026 | 2026-08-26 Talent analytics powered by Metix AI · Series reports
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