// Upto 4x Faster · Apache Spark™

Spark at full speed,
now with AI.

One engine, everywhere. Spark re-imagined with storage awareness across every pipeline stage, on an optimized fork of Velox. Up and running on your existing Spark in minutes — no migration, no rewrites. AI superpowers in the Spark UI.

Create an account → View docs

quanton — ask me anything

!helm upgrade --install quanton-operator \

oci://registry-1.docker.io/onehouseai/quanton-operator \

--namespace quanton-operator \

--create-namespace \

-f onehouse-values.yaml

✔ Release "quanton-operator" deployed

✔ SparkApplication CRD registered

✔ Quanton engine active

— Ask anything (e.g. "how fast is it?")

// Works with

// Features

⚡

Going beyond vectorized execution

Vectorized native execution on an optimized fork of Meta's Velox engine — already proven at monstrous scale. Plus the storage-aware optimizations vectorization alone can't see.

☸

Runs Anywhere

Run in the cloud or on-prem using our Kubernetes operator built on the kubeflow SparkApplication CRD. Or directly run it in your existing Spark platform.

🧠

AI Spark Engineer, embedded

Lives inside the Spark UI with live access to configs, runtime, heap, and GC. Backed by a knowledge server trained on a decade of Spark and lakehouse expertise.

Quanton optimizes every stage of the pipeline: the read, the compute, and the write.

E Extract — read

~7× lower scan time on TPC-DS q23 — network I/O overlapped with compute, minimal scheduling overheads. Merge-on-Read queries several times faster than OSS.

T Transform — compute

Faster Velox operator implementations, new operators for index-aware joins, and storage-aware plan reshaping -- compound into 2-4x faster transformation speeds.

L Load — write

Native writes to Hudi and Iceberg — low-shuffle MERGE ~6× faster at 1 TB. Dynamic acceleration auto-tunes storage, indexes, and metadata based on your write patterns.

See how Quanton stacks up against every other way to run Spark →

// Benchmarks

open-source-spark │ quanton

TPC-DS 10TB · EKS · 32 vCPU

0.0×

Faster Execution

vs. open-source Spark on TPC-DS, TPCx-BB, TPC-DI, LakeLoader

Compute Cost Reduction

achieved by Fortune 500 companies in production

Petabytes

Data Processed Per Day in Production

on battle-tested Spark infrastructure

// AI co-pilot

AI assistance
for every Spark job.

Quanton AI watches every job, diagnosing issues in real time, and guiding you from your first DataFrame to debugging large-scale production pipelines.

Sees every signal, live

Streams logs, stage DAGs, executor metrics, task timelines, shuffle stats, and JVM/GC into a single live picture of your job.

Diagnoses, then prescribes

Pinpoints OOMs, skew, fetch failures, and broadcast timeouts — then recommends repartitioning, executor sizing, memory tuning, and AQE fixes that move the needle.

Skills built for Spark engineers

Dozens of tools for query plan analysis, SQL execution, JVM and PySpark debugging, and Open Table Formats storage tuning — the work you actually do.

Your keys. Your data.

Bring your Claude or OpenAI API key — stored in your browser. Prompts and AI data never touch our servers.

// Pricing

Radically fair
pricing.

Pay by GB processed, not by compute hours burnt — every speedup we ship cuts your infra bill while keeping your Quanton bill flat. Quanton runs in your own Kubernetes, so spot and reserved-instance savings stay yours, not ours — up to 70% on top.

cost = GB_processed × rate

THAT'S THE ENTIRE BILLING MODEL

Compute billing — 4× faster = 75% less revenue.

Per-GB billing — speed is free to give.

See full pricing →

* Estimates for illustrative purposes only. Actual costs vary by workload, usage, and vendor pricing.

Compute hours × DBU markup rate $96,291.00

Mandatory support tier $5,250.00

Subtotal$101,541.00

ANNUAL AMOUNT DUE$101,541.00

OVERPRICED

40,000 GB × markup rate $34,000.00

Support included

Subtotal$34,000.00

ANNUAL AMOUNT DUE$34,000.00

YOU SAVE $67K

// Community

You're not alone
in this.

We've been where you are — pioneering the Lakehouse and running planet-scale ones at Uber and LinkedIn. Now we show up in your Slack, merge PRs fast, and take Spark seriously.

💬

Talk to us

Ask the team who built Quanton. Real engineers, real answers, no sales pitch.

Slack async

The team who built Quanton, in your DMs.

Join us on Slack →

Office Hours live · weekly

Open Q&A every Wednesday at 9 AM PT.

View schedule →

⚡

Try it yourself

Skip the chit-chat. Spin up a cluster on your laptop and see the speed difference in under 10 minutes.

$ helm upgrade --install quanton-operator

✔ Done. Run your first Spark job.

⏱ ~4 minutes from zero to running

View on GitHub →

Ready to make Spark fast?

Deploy the Quanton Operator in under 10 minutes.

Create an account → Talk to us

// Customer impact

Click a card or use the arrows to explore.

✈️

Large US Airlines

EMR → Quanton on EKS

"We cut our Spark infrastructure bill in half and freed up millions of core-hours. The migration was drop-in — no job rewrites."

— VP of Data Engineering

60%

Cost savings vs EMR

3.8M

Core-hours saved/year

💳

Fintech Customer

EMR → Quanton on EKS

"Eight hundred thousand dollars in annual savings and our jobs run nearly twice as fast. It's not even close."

— Head of Platform Engineering

$800K

Annual savings vs EMR

45%

Faster Spark jobs

📡

Global Telecom

Databricks → Quanton on EKS

"10× the performance off Databricks, and we now hit 15-second ingest latencies we could never achieve before."

— Principal Data Architect

10×

Perf vs Databricks

15s

Ingest latency

🤖

AI Note Taking SaaS

EMR → Quanton on EKS

"Processing a petabyte a day at half the cost — Quanton made our real-time AI pipeline actually viable at scale."

— CTO

1PB

Processed per day

50%

Cost savings vs EMR

🏥

Healthcare Analytics Co.

DIY K8s → Quanton on EKS

"We were drowning in compute costs running compliance pipelines across 40 million patient records. Quanton cut our nightly runs from 6 hours to under 90 minutes."

— Director of Data Platform

4×

Faster nightly runs

55%

Infra cost reduction

Spark at full speed,now with AI.