Companies · Data / Analytics
San Francisco · CA, USA · Data / Analytics · founded 2022 · https://www.denormalized.io/
Diligence memoA one-page analyst read on Denormalized — recommendation, valuation, rhythm, risks.→Denormalized: limited disclosed financing to assess.
Synthesized from the figures below est. — every claim rests on a number shown on this page.
Denormalized is one of 41 Data / Analytics companies tracked from San Francisco, CA, USA, on record since 2022. By capital raised it ranks in the upper tier (ahead of 76% of sector peers), and in the upper tier by modeled valuation est..
Ranking is computed against this company's own sector cohort — reported capital is fact; valuation tiers are modeled.
AI analyst read est. — model-extracted from this company's public description, not a verified fact. 30%
operates a technology-led product inferred from public copy
Grounded in: “You are a venture analyst”
serverless platform for real-time data
Denormalized is a serverless real-time data platform that allows users to query data quickly while eliminating the need to manage complex infrastructure. It enhances developer productivity by automating schema inference from sample data and simplifying data stream creation allowing engineers to go from idea to production fast. Denormalized supports SQL for data transformations without needing complex stream processing systems like Flink.
As reported in public records reported — not modeled.
Solid bars are reported offering amounts reported; hatched bars are the modeled post-money valuation est. — both on one shared scale so you can read raise-vs-worth at each round directly. Use the toggles to overlay data labels and the niche-peer / market average value lines.
No round amounts on record to chart.
No staged rounds to sequence.
Round size and date are reported; the stage label is inferred from round size. Valuation is modeled from stage benchmarks. Directional, not a quoted figure.
Not enough modeled valuation points to chart a trajectory.
Benchmarked against 41 companies in Data / Analytics. Each bar is a median (the middle company, not an average — outliers don't skew it). Two yardsticks: real money raised (reported on Form D) and modeled value (our estimate est.). These are whole-sector medians across all stages, except the per-stage row.
Raised more than 76% of sector peers (real $). Modeled value above 76% of peers (estimate).
Stage is inferred from round size est., not reported on the filing — a round's dollar size maps to a bucket: Pre-Seed <$1.0M · Seed $1.0M–$4.0M · Series A $4.0M–$15M · Series B $15M–$40M · Series C $40M–$100M · Series D+ $100M–$400M · Growth/Late >$400M.
| Stage | Amount · real | Announced | Post-money · est | Value · est | Conf. |
|---|---|---|---|---|---|
| No rounds recorded. | |||||
Predictive signals are modeled est. from this company's own cadence and step-up, plus sector benchmarks — directional, not advice. Peer set and a CSV export live in your analyst workspace.
Denormalized is an official record sourced from the U.S. Securities and Exchange Commission (SEC). U.S. data is aggregated from SEC Form D filings.
Nearest neighbours across the whole database — matched on sector, stage and capital scale, and on shared operators (officers or directors named at both companies in public filings). A discovery shortlist, not a valuation cohort — verify before acting, the same way modeled figures are directional.
| Company | Sector | Stage | Raised · real | Value · est | Why similar |
|---|---|---|---|---|---|
| Artie, Inc. | Data / Analytics | Series B | $36.0M | $742.0M | same sector |
| BeatDeck | Data / Analytics | — | — | — | same sector |
| Big Data Analytics, Inc. | Data / Analytics | Pre-Seed | $252K | $11.4M | same sector |
| Bracket | Data / Analytics | — | — | — | same sector |
| Brewit | Data / Analytics | — | — | — | same sector |
| Briefer | Data / Analytics | — | — | — | same sector |
| CareerTu | Data / Analytics | — | — | — | same sector |
| Castled.io | Data / Analytics | — | — | — | same sector |
Matched by meaning, not labels — a local language model reads each company's name, sector and description and ranks the closest in that learned space. This catches look-alikes that cross sector boundaries; the structured list above explains its matches, this one trusts the text. Directional, like every modeled signal here.
| Company | Sector | Stage | Value · est | Match |
|---|---|---|---|---|
| Hydra Serverless Analytics on Postgres | — | — | — | 72% |
| Lariat Data Observability for Data Engineering Teams | Developer Tools | — | — | 70% |
| Defer Zero infrastructure background processing platform. | SaaS / Software | — | — | 69% |
| Realm Better data structures = no DB. | — | — | — | 69% |
| ZeroStorefront #1 Data platform for restaurants. Acquired by Thanx | Food & Beverage | — | — | 69% |
| Simplifyd Systems We deliver toll-free internet apps | Software / Tech | — | — | 68% |
| PipelineDB Open-source time-series data analytics extension for PostgreSQL | Data / Analytics | — | — | 68% |
| RethinkDB The open source database for the realtime web. | — | — | — | 68% |
See where Denormalized sits in the wider market — its sector, location and stage cohorts, each with their own leaderboards and capital-flow timelines.
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