dbt Labs

Creator of dbt (data build tool), the open-source SQL transformation layer used by 30,000+ data teams at Airbnb, JetBlue, and GitLab. Series D at $4.2B (Feb 2022, Altimeter Capital); ARR ~$60M on dbt Cloud with over 50,000 paying users. Central to the modern data stack alongside Snowflake, Databricks, and Fivetran — every analytics engineer uses dbt.

Data/Cloud🇺🇸 United StatesFounded 2016ISO/NSO equitygetdbt.com ↗

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Reviewed May 24, 2026 (2d ago)

Current estimate

4 methods · May 24, 2026Medium confidence (36%)

$2.5B

range $0.5B – $4.6B⚠ methods disagree (4.8× spread)

Implied per-share: $14.1 · vs last primary -39%

This estimate reflects what informed investors are paying on secondary markets like Hiive and Forge — not the 409A valuation on your grant letter.

Last primary round

$4.2B

Series D · 51mo ago

Secondary signal

$2.6B

Forge · 2026-04-38%

Sourced from Forge/Hiive public data. Full order books require a paid subscription; figures shown are best-effort from public disclosures.

Headcount

650

employees · LinkedIn-7%

LinkedIn count — directional proxy only. Historical figure sourced via Wayback Machine; treat ±15% as normal variance.

Revenue (est.)

$60M

annual run rate · est.

Complete company data

Every input we use, where we got it from, and how much we trust it.

Field	Value	Source	Confidence
Company fundamentals
Sector	Data/Cloud	Editorial classification	high
Headquarters	🇺🇸 United States	Company website · Crunchbase	high
Founded	2016	Company website · Wikipedia	high
Website	getdbt.com	Direct	high
Latest primary round
Post-money valuation	$4.2B	TechCrunch Feb 2022	high
Round name	Series D	TechCrunch Feb 2022	high
Date	2022-02-24 (51 months ago)	TechCrunch Feb 2022	high
Lead investor	Altimeter Capital	TechCrunch Feb 2022	high
Amount raised	$222M	TechCrunch Feb 2022	medium
Capitalization
Total fully-diluted shares	180M	SEC Form D · secondary price math · cap-table leaks › notes Public total fully-diluted share count: estimated from SEC Form D filings, secondary-market pricing math (implied valuation ÷ price per share), and leaked cap-table summaries. Considered the lowest-confidence input.	low
Implied share price (latest primary)	$14	Valuation × 1000 / share count (= $4.2B ÷ 180M)	medium
Primary equity type granted	ISO/NSO	Public reports of company equity practices	high
Financials
Annual revenue (est.)	$60M	Sacra · The Information · press leaks › notes Annual revenue: best public estimates from Sacra, The Information, WSJ leaks, or company-stated ARR. Where official, we cite the source on the funding round.	medium
EV / Revenue (implied)	70.0x	Computed from valuation ÷ revenue	medium
Headcount
Employees (now)	650	LinkedIn — current company page count › notes Headcount: LinkedIn 'Company' page employee count, taken now and approximately 12 months ago via the Wayback Machine. Treat as a directional proxy for revenue growth, not a hard number.	medium
Employees (12 months ago)	700	LinkedIn via Wayback Machine	medium
12-month headcount growth	-7%	Computed	medium
Methodology inputs
Sector ETF proxy	WCLD	Editorial choice — most representative public ETF › notes Sector ETF: editorial choice of the most representative public-market proxy. Annual return: 3-year trailing average from Yahoo Finance, refreshed quarterly.	medium
ETF annual return (trailing 3-yr)	1%	Yahoo Finance · refreshed quarterly	medium

Funding history

Primary rounds reported in Bloomberg, WSJ, TechCrunch, Reuters, or SEC Form D filings (efts.sec.gov). Linked per round below.

Valuation progression (equity rounds)

Valuation progression · equity rounds

$4.2Blatest · Series D

Total growth

105×

Our estimate

$2.5B

Primary round

Down round

Our estimate

Series D+171%2022-02-24

$4.2B

Led by Altimeter Capital · raised $222M

Source: TechCrunch Feb 2022

Series C+869%2021-06-21

$1.6B

Led by Altimeter Capital · raised $150M

Source: TechCrunch Jun 2021

Series B+300%2020-09-01

$0.2B

Led by Andreessen Horowitz · raised $29.5M

Source: TechCrunch Sep 2020

Series A2019-04-01

$0.0B

Led by Andreessen Horowitz · raised $12M

Source: Crunchbase

Secondary market signals

Secondary market signals: bid/ask/trade indications from Hiive (hiive.com), Forge Global, Caplight Index, and tender prices reported in the press.

Implied valuation over time

Implied valuation · secondary market

$2.6B+7% vs first recorded

Trade

⚠

Forge and Hiive publish aggregated market data publicly, but full order books, individual bids/asks, and confirmed trade prices require a paid account. The figures below are sourced from their public summaries, press-reported tender prices, and SEC disclosures. They represent the best publicly available signal — not a guaranteed executable price.

Date	Type	Source	Price / share	Implied valuation
2026-04-22	trade	Forge	$15	$2.6B
2026-02-18	trade	Hiive	$14	$2.4B

View live indications: Hiive ↗ · SEC Form D filings ↗

Public peer comparables

Public peer comparables: editorial selection of public companies with the closest business model. EV/Revenue and growth from public 10-Q filings and Bloomberg, refreshed quarterly.

Ticker	Company	EV / Revenue	Revenue growth	As of
DDOG	Datadog, Inc.	21.55x	+32%	2026-05-20
MDB	MongoDB, Inc.	10.66x	+27%	2026-05-20
NET	Cloudflare, Inc.	32.81x	+34%	2026-05-20
SNOW	Snowflake Inc.	12.74x	+30%	2026-05-20

Confidence breakdown

How much we trust each of the four valuation methods for this specific company, and why.

Method A — Peer-multiple

weight 25%→ $0.9B23% confidence

↳ Effectively excluded from the blend — this method is structurally unreliable for this company.

Growth-weighted peer EV/Revenue: 20.1x → 25% private-company discount → 15.1x on $60M revenue. Output implies less than half the recent market anchor ($3B) — this company is likely valued on optionality / non-revenue factors and Method A is structurally less reliable here.

Method B — Secondary-implied

weight 45%→ $2.5B55% confidence

Recency-weighted average of 2 secondary indications (180-day decay)

Method C — Primary time-decay

weight 20%→ $3.4B20% confidence

↳ Effectively excluded from the blend — this method is structurally unreliable for this company.

$4.2B round (2022-02-24) × 5.60× growth × 0.85× multiple decay over 4.3 years — capped at 1.3× recent secondary ($2.6B → $3.4B)

Method D — Sector momentum

weight 10%→ $4.4B10% confidence

↳ Effectively excluded from the blend — this method is structurally unreliable for this company.

$4.2B × (1 + 1% p.j.)^4.3yr = $4.4B via WCLD ETF-proxy

Overall confidence

36%

Weighted average of the four methods. Above 65% is high, 40–65% medium, below 40% low.

Medium

Worked example for an employee

A concrete walk-through using a hypothetical employee profile. Same engine the calculator uses — try it with your real numbers.

Profile: a hypothetical employee who joined dbt Labs 24 months ago (2024-05-26) with 2,000 options, on the standard 4-year vesting schedule with a 1-year cliff.

Vesting

1,000 of 2,000

50% vested at month 24

Implied share price (mid)

$14

weighted average of 4 methods

Gross vested value

$14,139

vested shares × implied price

Net value

$14,139

no strike, gross = net

Tax (rough)

$1,465

US federal only · AMT risk: low

What if the next round is…

Up round +30%

$15,983

New round at +30% valuation, 15% new shares issued

Down round −30%

$8,248

New round at −30% valuation, 20% new shares (higher dilution in distress)

Secondary today

$12,018

Sale on the secondary market at the typical 15% discount to the mid estimate

These numbers come from the same engine as the live calculator. Walk through with your own grant: use your real numbers →

Transparent assumptions

What we assumed where exact data isn't available. If any of these don't match your situation, the numbers above will be off.

Fully-diluted share count

180M shares

We don't have authoritative cap-table access for private companies. The number above is reconstructed from SEC Form D filings, secondary-market price-vs-valuation math, and leaked share-class summaries. Actual fully-diluted count (including unvested option pool and SAFEs) may differ by 5–15%.

Common-stock waterfall

1.0× to common

We assume a clean common-stock outcome — i.e. preferred-share liquidation preferences and ratchets do not extract value before common. In a down-exit, this assumption can be very wrong: preferred stack can take 30–70% of proceeds.

Private-company illiquidity discount

25% off public peers

Applied to Method A (peer-multiple). Per-company because category leaders with deep secondary markets and a clear IPO path warrant a smaller discount than early-stage names. The literature range is 10–35%; for dbt Labs we use 25% based on secondary-market depth, valuation history, and proximity to liquidity.

Revenue growth assumption (Method C)

50% YoY

Compounded forward from the last primary date to today to estimate the company's value drift. Set per-company based on disclosed or reported ARR trajectory. Method C is further capped at 1.3× the most recent secondary trade (if any) to stop runaway extrapolation when revenue growth outpaces what the market is actually paying.

Sector ETF momentum (Method D)

WCLD @ 1%/year

Method D applies the trailing return of WCLD as a market-proxy adjustment to the primary valuation. Crude — meant as a tiebreaker when peer and secondary data conflict, not as a primary signal.

Outlier auto-downweight

Methods >50% from median get ½ weight

Robust-statistics safety net: any method whose output strays more than 50% from the median of the other three methods has its confidence weight halved when computing the blended mid-point. Prevents a single bad extrapolation from dragging the headline.

Recency decay for secondary trades

180-day half-life (e⁻ᵈ/¹⁸⁰)

A trade from 30 days ago counts ~5× more than one from 180 days ago. Tunable; some platforms use shorter half-lives.

Tax estimate

US federal only, single filer

Uses 2024 US federal brackets, ignoring state tax, NIIT, AMT credit recovery, and any other deductions. Treat as a directional sanity check, not a tax bill.

All data from public sources. Not investment, tax, or legal advice. Not affiliated with dbt Labs. Last refreshed manually — see methodology for our update cadence.