HireTop · Jul 2025
A profile of ParaQuery’s product, founder background, and YC Spring 2025 positioning; it reiterates the no-migration, GPU-accelerated Spark/SQL pitch and the New York base.
Managed GPU-accelerated Spark + SQL at 2x speed and half the cost
Public company, workplace, funding, and market signals
Updated Jul 29, 2026
ParaQuery (Hypermorphic, Inc.) is a New York-based, YC-backed startup building a fully managed GPU-accelerated Spark + SQL platform that aims to make data processing faster and cheaper without data migration.
Primary product
Fully managed GPU-accelerated Spark + SQL data processing platform
Founded
2023
Headquarters
New York City, New York, United States
Team size
1-10 employees
Industry
Data Infrastructure and Analytics
Sub-industry
Big data processing / enterprise data infrastructure
Business model
0 jobs at ParaQuery
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Stage
seed / pre-seed
Total raised
$500K
Latest round
Seed · Jun 2025
Latest amount
$500K
Jun 2025 · Y Combinator
Leadership
Founder and CEO
Investors
Public messaging emphasizes efficiency, performance, and user-friendliness; the company also describes a white-glove, risk-free, early-access motion.
Pricing
Not publicly fixed; early pricing was discussed as bytes scanned or compute time, with enterprise licensing also mentioned as a possibility.
Differentiators
Technology
Customers
Competitors
HireTop · Jul 2025
A profile of ParaQuery’s product, founder background, and YC Spring 2025 positioning; it reiterates the no-migration, GPU-accelerated Spark/SQL pitch and the New York base.
Hacker News · May 2025
Launch discussion for ParaQuery. The founder described a fully managed GPU-accelerated Spark + SQL product, claimed large cost and runtime improvements over BigQuery, and said the company was operating a waitlist/early-access model.
Y Combinator on LinkedIn · May 2025
YC promoted ParaQuery as a GPU-accelerated data processor, highlighting cost savings, speedups, and the founder's background in developer tools and distributed systems.
Y Combinator
Official YC launch page describing the product as a GPU-accelerated Spark + SQL engine with up to 5x cost-efficiency claims versus BigQuery and cloud-agnostic deployment.