Databricks 25x, Snowflake 12x: Understanding the NAV Trap in Private Markets

Private markets are having a moment.
Retail money is flowing in, valuations are climbing, and access has never felt easier.

But beneath the surface, something important is happening that most people are missing.

This is not just a valuation story.
This is a structure story.


What’s actually going on

Over the past couple of months, a small group of private giants has pulled in massive demand:

  • Stripe marked up to ~$159B in its latest tender
  • Anthropic raised at ~$380B
  • Databricks sits at ~$134B
  • SpaceX + xAI combined at ~$1.25T

At the same time:

  • Retail-focused funds like BXPE, VCX, and DXYZ are seeing strong inflows
  • Secondary markets are active, but still relatively thin
  • NAVs across these funds keep moving higher

On the surface, it looks like healthy price discovery.

It isn’t that simple.


The core issue: NAV is not price

Most investors treat NAV like a real, tradable price.

But in private markets, NAV is closer to an estimate than a market-clearing number.

Here’s how the system actually works:

  • Secondary trades happen in small volumes
    Even the most active names trade in limited size

  • Those trades are used as reference points
    Platforms aggregate them and create “market prices”

  • Funds use those inputs to mark NAV
    Along with models and internal assumptions

  • Investors transact at NAV
    Buying and redeeming based on those marks

  • New inflows go back into the same ecosystem
    Supporting future secondary prices

That creates a loop.

Not illegal. Not broken.
But not pure price discovery either.


Why the multiple gap matters

Let’s take a clean example:

  • Databricks

    • ~$5.4B revenue run rate
    • Growing ~65%
    • Valuation implies ~25x revenue
  • Snowflake (public comp)

    • ~$4.7B revenue
    • Growing ~29%
    • Trades ~11–12x revenue

Yes, Databricks is growing faster.

But the gap is still large.

Even with strong growth assumptions, a more conservative framework gets you closer to $90–100B, not $134B.

Same pattern with Stripe vs Adyen:

  • Stripe trading at high-teens to 20x revenue
  • Adyen sitting in single digits with stronger margins

The takeaway:

  • Private valuations are 2–3x public comps
  • That gap is being sustained by the system itself

The feedback loop no one talks about

The ecosystem reinforcing these valuations looks like this:

  • Step 1: Thin secondary trades set direction
  • Step 2: Aggregators convert that into pricing signals
  • Step 3: Funds mark NAV using those signals
  • Step 4: Retail invests based on NAV
  • Step 5: That capital flows back into the same names

And then it repeats.

Important point:

  • Most unicorns trade below their last round in secondary markets
  • A handful of mega-cap names are the exception
  • Those few names are holding up the entire category

That dispersion is the real signal.


Why this cycle hasn’t been tested yet

In earlier cycles:

  • Public markets corrected
  • Private markets adjusted slowly

But companies could stay private and wait it out.

Today is different:

  • Public markets are relatively stable
  • But large private companies are about to go public

That changes everything.

Because:

  • A public listing creates a real, liquid price
  • That price becomes the benchmark for everyone else

The next 120 days matter more than the last 3 years

There are four key triggers ahead:

  • Anthropic revenue clarity
    How revenue is defined will directly impact its multiple

  • SpaceX roadshow (June 2026)
    First real test of valuation against public investors

  • SpaceX listing (July 2026)
    A live market price replaces model-based marks

  • OpenAI IPO (target Q4 2026)
    Could anchor the entire AI valuation stack

One print can reset the whole cohort.


Why this matters for investors

This isn’t about calling tops or bottoms.

It’s about understanding structure.

If you’re investing through funds

  • Redemption is not unlimited

    • Typically capped around 3% per quarter
  • Liquidity depends on flows

    • Not just underlying asset value
  • Overlapping exposure matters

    • Many funds own the same names

If you’re buying in secondary markets

  • Spreads can widen quickly during repricing
  • Discounts can appear before public listings
  • Early signals often show up in small trades

If you’re allocating larger capital

  • Stress testing becomes critical

    • What happens if multiple funds face redemptions together
  • NAV should be treated as a model output

    • Not a guaranteed exit price

The counter view is not wrong

There is a strong argument on the other side:

  • These are category-defining companies
  • AI is creating new economics
  • Public comps may not fully capture that
  • Retail access demand is real and structural

And yes:

  • If IPOs validate current valuations, the premium holds

But here’s the catch:

  • That validation hasn’t happened yet
  • And the system hasn’t been tested under pressure

What to watch going forward

Instead of reacting to headlines, focus on signals:

  • Secondary trades clearing below last rounds
  • Changes in IPO pricing vs expectations
  • Fund redemption activity
  • NAV vs market price gaps (especially in listed vehicles)

Final thought

Private markets today feel liquid.
They feel accessible.
They feel like price discovery is happening in real time.

But a lot of that confidence is built on internal marks and limited trades.

The next phase is different.

  • Real buyers
  • Real sellers
  • Real liquidity

When that happens, the loop either:

  • Holds and gets validated
    or
  • Breaks and resets valuations across the board

Either way, we finally get an answer.

And that’s what makes the next few months worth watching closely.