QuestDB Financial Model
Dev Tools Startup Financials (Free Excel Download)
Open-source, high-performance time-series database built for extreme ingestion speed and low-latency SQL queries.
professionals from Deloitte
Used by professionals from
About this model
QuestDB is an Apache 2.0 open-source time-series database written in Java and C++ after six years of R&D. It differentiates on fast ingestion, standard SQL, and a small footprint for finance, industrial, mobility, data-science, and operations workloads requiring high throughput and low latency.
The company was pre-revenue, with a hosted cloud SaaS product and enterprise features planned on top of the OSS base. Its developer-led strategy uses community adoption and lighthouse relationships before enterprise upsell; the research gives no pricing, paying customer count, or current licence revenue.
From August 2020 to May 2021, deployments rose from 500 to 5,500, demo users from 1,000 to 16,000, and GitHub stars from 1,200 to 4,700. Airbus and Yahoo are named users. The model should forecast deployments, cloud conversion, workloads, licences, infrastructure cost, churn, and adoption.
A turnkey financial model
Live formulas, no hardcoded values
Outputs are driven by live formulas, so the workbook updates from its assumptions instead of relying on hardcoded results.
All assumptions in one tab
Inputs are clearly marked in the Assumptions tab and separated from calculations, making it clear what to change and what to leave intact.
Statements always balancing
For integrated-statement models, the balance sheet, cash flow, and supporting schedules tie through properly.
Distinct schedules for clarity
Debt, working capital, taxes, and cash flow can get messy quickly. We group calculations in clear schedules, not across disconnected tabs.
No hidden macros or external links
There are no unexplained external workbook links or macros to undermine auditability or portability.
Changes flow through the model
Update a key driver and see the impact carry through the forecast, financing, and return outputs. We never use hardcoded numbers in formulas.
About QuestDB
questdb.io
How to build a detailed financial model for QuestDB
A complete walkthrough of the business, drivers, and assumptions behind the downloadable QuestDB model - distilled from its pitch deck and publicly available information.
Product & value proposition
- Time-series database written from scratch in Java/C++ over 6 years of R&D; 300k lines of code.
- Key differentiators: (1) fastest ingestion rate vs. InfluxDB and TimescaleDB at 100, 1M, and 10M device scale (benchmark: Time Series Benchmarking Suite); (2) standard SQL interface (no proprietary query language); (3) tiny footprint vs. competitors; (4) Apache 2.0 licensed.
- Deployment: self-hosted OSS today; fully hosted cloud and enterprise features on roadmap.
- Team from low-latency trading desks at HSBC, UBS, Morgan Stanley, Merrill Lynch, bp - claim enterprise understanding of high-throughput/low-latency needs.
Market
- No explicit TAM/SAM/SOM figures in deck.
- Market context provided directionally: Time-series is the fastest-growing database category on DB-Engines popularity index (Nov-18 → May-21), rising from ~100 to ~200 vs. flat/slow growth for Relational, Search, Document, Graph.
- 79% of time-series databases tracked on DB-Engines are open-source; 21% closed-source.
- Use-case volumes cited: Manufacturing - 3M metrics/min/sensor; FinTech - 10B daily market data updates; Asset Tracking - 500M daily device position updates.
Revenue model
- No current revenue disclosed. Pre-revenue at time of deck.
- Planned monetisation:
- Fully hosted cloud solution (SaaS, usage-based expected).
- Enterprise features (likely seat/subscription licence over OSS core).
- Go-to-market: developer-led / OSS community → lighthouse customer relationships → enterprise upsell; target verticals: FinTech, Data Science, Industrial, Mobility, ITOps.
Traction & metrics
All metrics are community/adoption - no revenue or paying customer counts disclosed.
| Metric | Aug-20 | May-21 |
|---|---|---|
| Unique deployed instances | 500 | 5,500 |
| Demo users | 1,000 | 16,000 |
| Slack members | 250 | 800 |
| GitHub contributors | 15 | 70 |
| GitHub stars | 1,200 | 4,700 |
- GitHub stars Sep-20 → Sep-21: ~1,800 → ~4,800+ (steep acceleration from Mar-21 onward).
- Community members (Orbit) Jun-19 → Jun-21: ~0 → ~5,000.
- Unique deployed instances Sep-20 → Sep-21: ~800 → ~5,000+.
- Headline claim: "Users grew by 500% since January [2021]".
- Named enterprise users: Airbus, Yahoo, Kepler Cheuvreux.
- #10 launch on Hacker News ever; GitHub release of the month.
Competition / moat
Competitors identified:
- InfluxDB: slow ingestion, proprietary query language, huge footprint, MIT licence.
- TimescaleDB: slow, SQL, huge footprint, Apache 2.0 + Timescale licence.
- kdb+ (kx): fast, proprietary language, tiny footprint, closed source.
- Amazon Timestream: very slow, SQL, huge, closed source.
QuestDB positioning: Fast + SQL + Tiny footprint + Apache 2.0 - only player combining all four.
Moat claims:
- 6 years R&D / written from scratch - high replication cost.
- Strong OSS community (5k+ members, 70 contributors) with YC OSS group backing (GitLab, Docker, Supabase, PostHog, NGINX, Fivetran, GitHub, Mattermost, InfluxDB, Citus, Armory).
- Advisory network: Tom Preston-Werner (GitHub), Sebastien Pahl (Docker), Alexis Ohanian (Reddit), Andrew Alexeev (NGINX), Paul Copplestone (Supabase), Sumedh Pathak (Citus/Microsoft), James Hawkins (PostHog), et al..
Team & funding ask / use of funds
- Founding team: low-latency trading desk background (HSBC, UBS, Morgan Stanley, Merrill, bp). Individual names not shown in deck.
- Prior funding: $2.3M Seed. YCombinator S20.
- Current ask: $12M.
- Use of funds:
- Developer adoption KPIs: GitHub stars, contributors, unique instances.
- Product: fully hosted cloud solution + enterprise features.
- GTM: customer development, lighthouse customer relationships, developer advocacy, content, partnerships.
- Hiring: customer success, dev rel, GTM, operations, core database, frontend, cloud engineers.
- Roadmap timeline (Now → Jun-22): Cloud MVP → Serverless cloud → ML + geospatial dimensions.
Recommended financial model
- Archetype + why: OSS-led SaaS - usage-based cloud + enterprise licence.
QuestDB is a classic open-core / PLG (product-led growth) company. Revenue does not exist yet; the model must project from zero through OSS funnel → cloud conversion → enterprise licence. The community-size and instance metrics are the leading indicators. Usage-based cloud (consumption of compute/storage/ingest volume) is the standard for time-series cloud DBs (InfluxDB Cloud, Timescale Cloud). Enterprise adds a seat/subscription tier on top for SSO, RBAC, SLAs.
- Forecast horizon & granularity: 5 years (2021–2026), quarterly for years 1–2 (product build + early cloud revenue), annual thereafter. Pre-revenue through ~Q1-Q2 2022 while cloud MVP ships.
- Key drivers & assumptions:
*OSS funnel:*
- Unique deployed instances: 5,500 at May-21; grow at 15–20%/month declining to 5%/month by Y3 - consistent with 500% YTD growth decelerating post-product-market fit.
- Cloud conversion rate: 2–5% of active instances convert to paid cloud - typical OSS-to-cloud conversion benchmark.
- Enterprise conversion rate: 0.5–1% of instances, or sourced via direct sales from lighthouse accounts.
*Cloud revenue (usage-based):*
- ARPU cloud: $500–$2,000/month per customer - benchmarked against InfluxDB Cloud / Timescale Cloud pricing tiers for mid-market data engineering workloads.
- Net revenue retention: 110–130% (usage grows as customers ingest more data over time).
*Enterprise revenue (licence):*
- ACV enterprise: $50k–$200k - consistent with enterprise time-series DB deals in FinTech/industrial verticals.
- Sales cycle: 3–6 months.
- Target lighthouse count by end Y1: 5–10 paying enterprise logos.
*Cost structure:*
- R&D: majority of headcount pre-cloud; 60–70% of OpEx Y1, declining to 40% by Y3.
- S&M: ramp from near-zero (PLG) to 25–30% of OpEx as enterprise sales team builds.
- G&A: 10–15% of OpEx.
- Gross margin: 65–75% at scale for usage-based cloud (cloud infrastructure cost embedded); 85–90% for enterprise licence.
- Hosting/COGS: scales with cloud revenue; benchmarked on AWS/GCP pricing for compute + storage.
*Funding:*
- $12M Series A; model runway against burn rate - 18–24 months to meaningful cloud revenue.
- Scenarios (Base / Bull / Bear - which variables flex):
- Base: Cloud MVP ships Q2-Q3 2022; 3% OSS-to-cloud conversion; 5 enterprise logos by end Y2; cloud ARPU $1,000/month.
- Bull: Faster OSS instance growth (viral developer adoption continues); higher conversion (6%); enterprise deals land via Airbus/Yahoo/Kepler Cheuvreux relationships; ARPU expands via usage.
- Bear: Cloud MVP delayed to Q4 2022; conversion 1%; enterprise sales cycle drags; competing InfluxDB/Timescale cloud offers cut into conversion; funding needed earlier than runway suggests.
- Required sheets / outputs:
- OSS Funnel - instances, community members, GitHub stars (leading indicators).
- Revenue Build - Cloud (usage-based ARR) + Enterprise (licence ARR); waterfall by cohort.
- P&L - Revenue → Gross Profit → EBITDA; quarterly Y1–Y2, annual Y3–Y5.
- Headcount Plan - engineering, cloud, sales, dev rel, G&A.
- Cash Flow & Runway - monthly burn, cash balance, months to next raise.
- KPI Dashboard - ARR, NRR, cloud customers, enterprise logos, CAC payback (once data available).
Frequently asked
Is the QuestDB financial model free?+
Yes. The QuestDB model is a free Excel (.xlsx) download with live formulas. Sign up with your email and the workbook is yours to keep, review, and edit.
What's included in the model?+
A 5-year monthly forecast with P&L, cash flow and runway, valuation (exit multiple plus a DCF cross-check), MOIC/IRR returns, and unit economics, with live formulas throughout.
How was this model built?+
It was built from QuestDB's pitch deck and publicly available information, then structured to investment-banking standards as a fully editable Excel model.
Can I change the assumptions?+
Yes. You can change assumptions and the live formulas will recalculate in the downloadable Excel model.
Have more financial modelling questions? Contact us
Created by ex-finance professionals
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