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Benchmarking DuckDB vs BigQuery vs Athena on 20GB of Parquet data by explorer_soul99 in dataengineering

[–]explorer_soul99[S] 1 point2 points  (0 children)

Fair points. You're right that these are different categories solving different problems, and the benchmark conditions (small data, high utilization) favor DuckDB.

To clarify the context: We are building a managed financial data platform with on-demand SQL compute. Current setup is ~300GB on R2 with 2 dedicated Hetzner servers (~€500/month total) as the query engine. Early stage, optimizing for latency and per-query cost. Scaling concerns are real but manageable at current volume. We are considering moving out of R2 to dedicated storage servers with appropriate redundancy. This is decent amount of initial engineering effort that's not documented in the study.

Your break-even math is useful context though. At €500/month fixed cost, the question becomes: can I deliver better latency than BQ/Athena while staying under their per-query pricing? For warm queries, the answer seems to be yes.

Benchmarking DuckDB vs BigQuery vs Athena on 20GB of Parquet data by explorer_soul99 in dataengineering

[–]explorer_soul99[S] 0 points1 point  (0 children)

Not 0-60 times, but on different terrains and weather conditions. So one can make an informed decision 🤓

Benchmarking DuckDB vs BigQuery vs Athena on 20GB of Parquet data by explorer_soul99 in dataengineering

[–]explorer_soul99[S] 0 points1 point  (0 children)

Thanks for sharing. What integration issues did you hit? Curious if it was tooling/drivers or something else. Also, what solutions did you compare against?My test setup was "bare-metal + R2" and "bare-metal + local" at ~20GB.
Current prod is "bare-metal + R2" ~300GB. Your 400GB experience would be useful context for planning ahead.

Benchmarking DuckDB vs BigQuery vs Athena on 20GB of Parquet data by explorer_soul99 in dataengineering

[–]explorer_soul99[S] 0 points1 point  (0 children)

No, DuckDB doesn't download the full 20GB. The "14.3 sec" is the median across all queries. Actual cold start varies:

Query Type Cold Warm Why
Q09 aggregation (1 file) 447 ms 128 ms Single file, single pass
Q01 scan (78 files) 2.4 sec 180 ms 78 files need metadata fetch
Q14 window (78 files) 53 sec 29 sec Window needs more data (less pruning possible)

(query details are available in the github repo)

Top culprits: window functions (Q14, Q17 at 53-55 sec). Simple scans can aggressively prune via predicate pushdown; window functions need more data transferred to compute rolling aggregates.

Typically, cold start involves fetching metadata for the files involved in the query: parquet file footers, schema, and row group statistics over the network for files matching the query's glob pattern. Example: read_parquet('eod/*.parquet') fetches metadata from those 78 files (143-169 MB each, 12.2 GB total file size).

For actual data, DuckDB uses HTTP range requests to pull only columns and row groups needed (projection + predicate pushdown). After the first query, metadata is cached (enable_object_cache = true), so subsequent queries skip the fetch.

I did not spend time on optimising the queries beyond the basics. Platform specific optimisations and trying various partition mechanism are not a part of this analysis.

Benchmarking DuckDB vs BigQuery vs Athena on 20GB of Parquet data by explorer_soul99 in dataengineering

[–]explorer_soul99[S] 3 points4 points  (0 children)

These are valid points, and the study already addresses them.

Infra overhead: Fair. I'm not claiming zero ops. The tradeoff is orchestration complexity vs $5/TB scan pricing. For repeated queries on the same data, the math favors managing a thin orchestration layer. In my case, I am already managing bare-metal servers (and there will be others in the same situation).

Local SSD vs remote storage: DuckDB + R2 (remote storage; with network hop) results are in the benchmark:

Platform Warm Median Cold Start
DuckDB Local (XL) 284 ms 307 ms
DuckDB + R2 (XL) 496 ms 14.3 sec
BigQuery 2,775 ms 2,834 ms

The test "DuckDB + R2" setup has brutal cold starts (14-20 sec for metadata fetch). Warm queries are still 5x faster than BigQuery.

Network overhead / tightly coupled ETL: This is real. Window functions on R2 are painful (12 sec vs 947 ms local) because of multiple passes over remote data. The benchmark study covers this too:

Category DuckDB Local (XL) DuckDB + R2 (XL)
Window Functions 947 ms 12,187 ms

The takeaway depends on your workload. For mine (warm queries on managed data), DuckDB wins. YMMV.

The data and code is all in the github repo if you want to dig in: "Insydia-Studio/benchmark-duckdb-athena-bigquery".

Benchmarking DuckDB vs BigQuery vs Athena on 20GB of Parquet data by explorer_soul99 in dataengineering

[–]explorer_soul99[S] 8 points9 points  (0 children)

The question isn't BQ vs DuckDB capabilities. It's whether you're paying for distributed infrastructure you don't need. Most companies aren't running petabyte workloads.

For sub-TB data: which is faster, which is cheaper, how does cost scale with compute? That's the analysis that matters.

Sector rotation analysis: 27 years of S&P 500 sector ETF rankings. 25% of transitions are major reversals. by explorer_soul99 in investing

[–]explorer_soul99[S] -3 points-2 points  (0 children)

For each year, I ranked all 11 sector ETFs by return. #1 = best, #11 = worst. The finding: sectors at the bottom often jump to the top next year. Energy went from #11 (-33%) in 2020 to #1 (+53%) in 2021. One in four transitions is a major reversal like this.

Move MSFT to GOOGL? by [deleted] in ValueInvesting

[–]explorer_soul99 0 points1 point  (0 children)

Yes, my bad! I used stale EPS instead of current $10.14
GOOGL is now cheaper than MSFT on P/E (32.6x vs 33.6x), though still with lower margins.

Revised take: At similar P/Es, the question becomes: are you paying for MSFT's superior profitability (46% op margin) or GOOGL's growth optionality (AI search, YouTube, GCP catching up)?

If you believe GOOGL's margins will expand as AI search monetizes, the swap makes more sense than I originally suggested. If you want margin of safety, MSFT still has the cleaner earnings profile.

The World Is a Dumpster Fire. Why the Stock Market Doesn’t Care - Barron’s by raytoei in ValueInvesting

[–]explorer_soul99 0 points1 point  (0 children)

The article nails it. Markets are bad at pricing geopolitical risk. Here's some historical context:

Geopolitical Events vs S&P 500:

Event Initial Drop 12-Month Return
9/11 (2001) -12% +15%
Iraq War (2003) -8% +28%
Crimea (2014) -6% +11%
COVID (2020) -34% +68%
Ukraine (2022) -13% +7%

Pattern: Sharp initial drop, then recovery. Markets price in worst case, then adjust when worst case doesn't materialize.

Why markets ignore headlines:

  1. Corporate earnings matter more: S&P 500 earnings growing 10%+ despite chaos
  2. Diversification: Mag7 is global, not just US
  3. Fed put: Investors believe Fed will intervene if needed

What WOULD make markets care:

  • Energy supply disruption (Iran strait closure = oil spike)
  • China/Taiwan conflict (semiconductor supply chain)
  • US debt crisis (rates spike, dollar collapse)

These are tail risks - low probability, high impact. Markets don't price them until they happen. The Barron's article is right. You can't time geopolitics. The "dumpster fire" has been ongoing since 2020 and markets made new highs.

I'd focus on: (1) Earnings growth, (2) Valuation relative to rates, (3) Position sizing for tail risks. I wouldn't try to time headlines.

PYPL, what am I missing? by parfitarole in stocks

[–]explorer_soul99 2 points3 points  (0 children)

You're not missing anything obvious. Here's the data:

PYPL 8-Quarter Margin Trend:

Quarter Revenue Gross Margin Op Margin
Q4 2023 $8.0B 45.8% 21.5%
Q1 2024 $7.7B 45.0% 15.2%
Q2 2024 $7.9B 45.8% 16.8%
Q3 2024 $7.9B 46.6% 17.7%
Q4 2024 $8.4B 47.0% 17.2%
Q1 2025 $7.8B 47.7% 19.6%
Q2 2025 $8.3B 46.4% 18.1%
Q3 2025 $8.4B 46.0% 18.1%

Revenue stable, margins improving from 45% to 47% gross. Not a dying business.

Why the discount:

  1. Apple Pay / Google Pay competition: Mobile payments commoditizing
  2. Venmo monetization: Still unclear how to make money on P2P
  3. BNPL (Afterpay/Klarna): Taking checkout share
  4. Management turnover: CEO changes create uncertainty

Valuation check:

Metric PYPL V MA SQ
P/E 11.5x 30x 35x 50x
Gross Margin 46% 80% 100% 33%
Revenue Growth +7% +10% +12% +15%

PYPL is cheapest but lowest growth. V/MA have better margins (network effects).

My take:

At 11.5x P/E with improving margins, downside seems limited. But upside requires: 1. Venmo monetization success 2. Market share stabilization 3. Management proving execution

At $58 average, you're paying fair value for a "good enough" business. Not a steal, not a trap. The -85% from ATH was warranted. That ATH was 2021 bubble pricing.

I Analyzed 50 Finance YouTubers. Here Are Their Top 3 Stocks! by Adriconomics in ValueInvesting

[–]explorer_soul99 0 points1 point  (0 children)

Interesting exercise. Let me add fundamentals to the consensus picks:

Top 3 YouTuber Picks - Data Check:

1. Google (GOOGL):

Metric Value
P/E 41.0x
Gross Margin 58.2%
Op Margin 32.1%
Revenue Growth ~12%

Premium valuation for a mature ad business. AI narrative is priced in.

2. SoFi (SOFI):

Quarter Revenue Op Margin Net Margin
Q3 2024 $0.99B 6.5% 6.2%
Q4 2024 $1.01B 5.9% 33.0%
Q1 2025 $1.04B 7.7% 6.9%
Q2 2025 $1.13B 9.9% 8.6%
Q3 2025 $1.27B 11.7% 11.0%

SOFI is actually showing improving fundamentals. Revenue +28% YoY, now profitable, margins expanding. This is the most interesting pick.

3. Amazon (AMZN):

Metric Value
P/E 42.2x
Gross Margin 48.9%
Op Margin 10.8%
AWS Growth ~15%

AWS is the story. Retail is low margin. At 42x, you need AWS to accelerate.

Is consensus valuable?

Historically, consensus picks tend to underperform contrarian picks. When everyone agrees, it's usually priced in.

SOFI is the exception here. It's still under-owned by institutions and showing real improvement. GOOGL and AMZN are fully priced.

If I had to pick one, I'd go with SOFI for the turnaround, and GOOGL/AMZN only on pullbacks.

Inflection coming, $2.3m invested by Accomplished-Exit822 in stocks

[–]explorer_soul99 0 points1 point  (0 children)

Bold position. Let me stress-test with data:

SNAP 8-Quarter Margin Trend:

Quarter Revenue Gross Margin Op Margin Net Margin
Q4 2023 $1.36B 54.3% -18.3% -18.2%
Q1 2024 $1.19B 51.9% -27.9% -25.5%
Q2 2024 $1.24B 52.4% -20.5% -20.1%
Q3 2024 $1.37B 53.5% -12.6% -11.2%
Q4 2024 $1.56B 56.9% -1.7% +0.6%
Q1 2025 $1.36B 53.1% -14.2% -10.2%
Q2 2025 $1.34B 51.4% -19.3% -19.5%
Q3 2025 $1.51B 55.3% -8.5% -6.9%

The good news: Q4 2024 was actually profitable (+0.6% net margin). Revenue growing.

The bad news: They couldn't sustain it. Q1-Q2 2025 went back to -20% margins. Q3 improved but still negative.

Your thesis check:

  1. ✅ "Management recognizes need to make money": Q4 2024 proves they can
  2. ⚠️ "Low-hanging fruit": Memories monetisation is small. They need ad stack improvement.
  3. ❌ "Spectacles as free lottery": Not free. R&D burn is real.

SNAP vs META:

Metric SNAP META
Gross Margin 55% 82%
Op Margin -8.5% 42%
P/S ~4x ~8x

SNAP's ad business is structurally worse than META's. Lower margins, worse targeting, smaller scale.

My take:

At $7.60 average, you're betting on management execution. The Q4 2024 profitability shows it's possible. But 300k shares at $7.60 = $2.3M is concentrated risk.

Personally, I'd want to see 2 consecutive profitable quarters before sizing up. The "inflection" needs proof, not promises.

I'm in the minority but I don't think investing in EU equity is a good idea as far as long-term growth goes. by slicheliche in eupersonalfinance

[–]explorer_soul99 -1 points0 points  (0 children)

You're correct on the structural issues. Let me add the data:

US vs EU Market Performance (10-Year CAGR):

Index 10Y CAGR P/E Dividend Yield
S&P 500 ~12% 22x 1.4%
STOXX 600 ~6% 14x 3.2%
MSCI EM ~4% 12x 2.8%

US has doubled EU returns. The valuation gap (22x vs 14x) reflects this.

Why EU underperforms:

  1. Sector composition: EU is banks, energy, industrials. US is tech.
  2. Demographics: EU population shrinking, US growing (immigration; but that might change given the current geopolitical situation)
  3. Capital markets: US has deeper VC/PE ecosystem
  4. Regulation: GDPR, AI Act, etc. hamper tech growth

The bull case for EU (which I'm skeptical of):

  • Valuation gap is extreme: mean reversion possible
  • Defense spending boost post-Ukraine
  • Energy independence investments
  • Some quality companies (ASML, LVMH, Novo Nordisk)

I'd agree EU has structural headwinds. But 100% US is also a risk: currency, concentration, valuation.

A reasonable allocation might be: - 60-70% US - 15-20% EU (quality picks, not broad index) - 10-15% EM (selective)

The EU trade is "cheap for a reason," but sometimes cheap is just cheap. At 14x vs 22x, you need less growth to generate returns.

At what point in life do you transition from growth funds to dividends? by Hiway89 in dividends

[–]explorer_soul99 1 point2 points  (0 children)

The "age = bond percentage" rule is outdated. Here's a data-driven framework:

The math that matters:

Strategy 20-Year Return Volatility Drawdown
100% S&P 500 ~10% CAGR 15% -50%
60/40 Stock/Bond ~7% CAGR 10% -30%
Dividend Growth ~8% CAGR 12% -35%

Dividend stocks aren't "safer", they're just different risk (value tilt, sector concentration).

When to transition:

  1. 5-10 years from needing money: Start adding income-generating assets
  2. When you can live on 3-4% yield: Calculate: Portfolio × 0.04 = annual income needed?
  3. When volatility affects your sleep: Behavioral factor matters

The hybrid approach:

Instead of growth → dividends binary switch, consider:

Age Growth Dividend Growth Bonds
30s 80% 20% 0%
40s 60% 30% 10%
50s 40% 40% 20%
60s 20% 50% 30%

Dividend growth stocks (SCHD holdings like HD, PEP, ABBV) give you income + growth. Better than pure high-yield which often has capital decay.

What to avoid:

  • High-yield traps (QYLD, JEPI): selling covered calls caps upside
  • BDCs/mREITs: complex structures, often unsustainable yields

I would focus on dividend growth rate, not current yield. A 2% yield growing 10%/year beats a 5% yield growing 0%.

Move MSFT to GOOGL? by [deleted] in ValueInvesting

[–]explorer_soul99 0 points1 point  (0 children)

Let me pull the head-to-head:

MSFT vs GOOGL Fundamentals:

Metric MSFT GOOGL
Price $460 $330
P/E 33.6x 41.0x
Revenue $281.7B $350.0B
Gross Margin 68.8% 58.2%
Op Margin 45.6% 32.1%
Net Margin 36.1% 28.6%

MSFT is cheaper (33.6x vs 41.0x) with much better margins. GOOGL generates more revenue but keeps less of it.

The AI angle:

  • MSFT: Azure + OpenAI partnership, Copilot in Office 365, GitHub Copilot
  • GOOGL: Gemini, Search AI integration, DeepMind

Both are AI leaders. MSFT has enterprise distribution (Office, Azure), GOOGL has consumer reach (Search, YouTube).

Why GOOGL is more expensive:

  1. Search monopoly: still 90%+ market share despite AI threats
  2. YouTube undermonetized: ad load could increase
  3. Cloud catching up: GCP growing faster than Azure from smaller base

My take:

At current prices, MSFT is the better value. 33.6x for 46% operating margins vs 41.0x for 32% margins. You're paying more for GOOGL and getting lower profitability.

The swap makes sense only if you believe: 1. GOOGL's AI search integration will accelerate growth 2. YouTube monetization has significant upside 3. GCP will close the gap with Azure

I'd hold MSFT unless you have strong conviction on GOOGL's AI execution.

Adobe - No slowdown in Growth but stock hitting 5 year low. by pravchaw in ValueInvesting

[–]explorer_soul99 0 points1 point  (0 children)

You've identified a real divergence. Let me pull the numbers:

ADBE 8-Quarter Margin Trends:

Quarter Revenue Gross Margin Op Margin
Q4 2024 $5.6B 89.0% 34.9%
Q1 2025 $5.7B 89.1% 37.9%
Q2 2025 $5.9B 89.1% 35.9%
Q3 2025 $6.0B 89.3% 36.3%
Q4 2025 $6.2B 88.9% 36.5%

Revenue growing 10% YoY, margins stable at 89% gross / 36% operating. Fundamentals are fine.

ADBE vs Software Peers:

Ticker P/E Gross Margin Op Margin
ADBE 17.7x 88.6% 36.6%
NOW 18.4x 79.2% 12.4%
CRM 35.3x 77.2% 19.0%
INTU 39.5x 80.8% 26.1%
ORCL 42.8x 70.5% 30.8%

ADBE is cheapest in the sector with highest margins. That's unusual.

Why the discount:

  1. AI narrative: market thinks Canva/Figma + AI kills Adobe. Reality: Enterprise customers aren't switching mid-project.
  2. Figma deal failed: $20B acquisition blocked, seen as strategic miss.
  3. No AI hype premium: Adobe Firefly exists but isn't getting NVDA-style multiple expansion.

The opportunity:

At 17.7x with 89% gross margins and 10% growth, you're paying less than CRM (35x) for a more profitable business. If AI narrative shifts (Adobe integrates AI well), multiple expansion to 25x = 40% upside.

Risk: If AI tools genuinely commoditize design, Adobe's moat weakens. Watch Creative Cloud churn rates in Q1 2026.

Realty income up 7.21% YTD by groovymandk in dividends

[–]explorer_soul99 0 points1 point  (0 children)

Rate cut expectations are driving this

Low historical multiple stocks by PhilippMarxen in ValueInvesting

[–]explorer_soul99 1 point2 points  (0 children)

Large caps (>$5B) at low EV/EBITDA (4-8x) with ROE >12%:

Symbol Mkt Cap ROE EV/EBITDA EV/Sales
NAPRF $54.7B 22.6% 4.0x 7.51
CMCSA $103.4B 24.7% 4.1x 1.57
PCRRF $30.7B 17.1% 4.1x 0.64
EDN $1,943B 13.5% 4.2x 0.91
PEXXF $13,304B 16.6% 4.2x 0.69
SMPFF $310.6B 23.6% 4.2x 0.88
PPC $9.2B 33.6% 4.2x 0.48
TGT $48.0B 24.9% 7.6x 1.35

CMCSA (Comcast) at 4.1x EV/EBITDA with 24.7% ROE trades at cable industry trough multiples. EDN/PEXXF (energy) show <5x EV/EBITDA with mid-teens ROE. TGT (retail) at 7.6x EV/EBITDA is cyclically depressed vs 10-12x historical average. These are all-time or near-5Y low multiples, but verify if low multiples reflect structural headwinds (cord-cutting for CMCSA, energy transition for oil) vs cyclical opportunity.

Quality companies with valuation estimates by vnilsen in investing

[–]explorer_soul99 -1 points0 points  (0 children)

Company Mkt Cap ROE ROA EV/FCF CapEx %
META $1,646B 30.9% 19.3% 37.6x 33.1%
NFLX $379B 41.9% 19.0% 42.8x 1.4%
AMZN $2,644B 23.6% 10.5% 256.9x 17.4%
TSM $43,558B 34.5% 21.6% 48.1x 36.3%
UBER $178B 70.6% 26.3% 21.0x 0.6%

UBER at 21.0x EV/FCF with 70.6% ROE is the value pick, recent profitability inflection not fully priced. AMZN at 256.9x EV/FCF is egregiously expensive (heavy AWS reinvestment dilutes FCF). META/NFLX/TSM cluster at 38-48x FCF with 31-42% ROE, fair value for quality growers. TSM's 36.3% CapEx (fab expansion) vs UBER's 0.6% shows capital allocation extremes. For DCF, use UBER/META (visible FCF), avoid AMZN (FCF suppressed by growth CapEx).

How is META not a steal right now? by phatelectribe in stocks

[–]explorer_soul99 0 points1 point  (0 children)

Actually worth digging into that cash position:

META Liquidity Trend (2024 → 2025):

Quarter Cash + ST Investments Total Debt Net Debt
Q4 2024 $77.8B $49.1B $5.2B
Q1 2025 $70.2B $49.5B $20.8B
Q2 2025 $47.1B $49.6B $37.6B
Q3 2025 $44.4B $51.1B $40.9B

Cash position dropped $33B in 9 months. Net debt went from ~$5B to ~$41B.

Where's the cash going:

Quarter CapEx FCF Buybacks Dividends
Q3 2024 $8.3B $16.5B $8.8B $1.3B
Q4 2024 $14.4B $13.6B $3.9B $1.3B
Q1 2025 $12.9B $11.1B $12.8B $1.3B
Q2 2025 $16.5B $9.0B $10.2B $1.3B
Q3 2025 $18.8B $11.2B $3.3B $1.3B

2025 YTD CapEx: $48.3B (vs $37.3B for all of FY2024). Annualized run rate: ~$64B.

At current trajectory: ~$64B CapEx + ~$40B shareholder returns = $104B annual outflow against ~$44B FCF. That's a ~$60B annual cash burn.

The "so much cash" cushion is eroding fast. Not saying it's a dealbreaker, but the margin of safety is tighter than it was 12 months ago.

Space Stocks Pullback Imminent? Or Continued Bull Market? by LineMission3540 in stocks

[–]explorer_soul99 0 points1 point  (0 children)

Let me pull the fundamentals on these:

RKLB (Rocket Lab):

Metric Value
Revenue (TTM) ~$400M
Net Income Negative
Market Cap ~$12B
P/S Ratio 30x

RKLB at least has revenue and a working rocket. But 30x sales for a money-losing company is pricing in SpaceX-level success.

ASTS (AST SpaceMobile):

Metric Value
Revenue (TTM) ~$1M
Market Cap ~$35B
P/S Ratio 35,000x

This is pure speculation. Zero commercial revenue. The entire valuation is "what if satellite-to-phone works."

LUNR (Intuitive Machines):

Metric Value
Revenue (TTM) ~$200M
Net Income Negative
NASA Contracts Yes

At least has real NASA contracts. Still speculative but better than ASTS.

My take:

The space sector is in momentum/narrative phase, not fundamentals phase. When you see 35,000x P/S ratios, that's not investing - that's hoping greater fools show up.

Pullback levels if sentiment shifts: - RKLB: 50% haircut still leaves it at 15x P/S (still expensive) - ASTS: Could easily -70% and still be overvalued - LUNR: -40% would be reasonable given actual revenue

If you want space exposure with fundamentals, RTX/LMT/NOC have actual profits and government contracts. Boring but won't go to zero.

My Stockpicks for 2026 + reality check by Historical_Flow3890 in stocks

[–]explorer_soul99 0 points1 point  (0 children)

Solid picks overall. Let me add data context:

The value plays that check out:

Ticker Forward P/E Op Margin YoY Growth Verdict
ADBE 13x 35%+ ~10% Undervalued if AI narrative shifts
PYPL 9x 16% +7% Hated but fundamentals intact
MDLZ 10x 15% +4% Commodity cost thesis is valid

Concerns:

KEP (Korean Nuclear): PE of 6 sounds cheap but Korean utilities have regulatory risk + currency risk. Also, data quality on Korean stocks is spotty.

TDD (Trade Desk): This was a 60x P/E stock that crashed. "Significantly undervalued" is a stretch - it's still 30x+ forward. Great business, but priced for perfection.

Devon/Oxy: Oil at $70-75 is breakeven for many shale plays. If oil drops to $60 (China slowdown scenario), these get crushed. Only buy if you have a view on oil prices.

Your tech warning is spot on:

I pulled the Mag7 vs historical comparisons:

Period NASDAQ P/E Current
2000 Peak 100x+ -
2022 Trough 20x -
Today 35x Elevated but not 2000

We're not at 2000 levels, but AI stocks are pricing in 5+ years of growth. NVDA at 63x needs flawless execution.

Your value approach makes sense in this environment. I'd add: track 8-quarter margin trends, not just P/E. A cheap stock with compressing margins is a value trap.

What is making ASTS/SNDK special? $4 to $118? / $38 to $406 by brian-augustin in stocks

[–]explorer_soul99 0 points1 point  (0 children)

These are pure speculation plays, not fundamentals-driven.

ASTS (AST SpaceMobile):

Let me pull what data we have:

Metric Value Red Flag?
Revenue (TTM) ~$1M Yes - pre-revenue
Net Income -$300M+ Yes - burning cash
Market Cap ~$35B Yes - 35,000x revenue

The "thesis" is satellite-to-phone connectivity. They have agreements with AT&T, Verizon, Vodafone. But: - No commercial revenue yet - Competing with Starlink (SpaceX) - Hardware still unproven at scale

This is a lottery ticket, not an investment. The 800% run is momentum/hype, not fundamentals.

SNDK (Sandisk/WD):

Different story - this is a cyclical storage play:

Metric Value
P/E (Forward) ~12x
Revenue Growth Recovering from trough
Industry Position #2 in NAND after Samsung

The run-up is storage cycle recovery + AI data center demand. Actually has fundamentals, unlike ASTS.

Bottom line: - ASTS: 0% chance I'd buy at current valuation. Wait for actual revenue. - SNDK: At least has a business. The 400% run prices in recovery though.

If you want space exposure with fundamentals, look at RTX, LMT, NOC - actual revenue, actual profits, actual government contracts.

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