Pay for data processed.
Not for hours burned.
Quanton bills on a single number: the volume of data your jobs read and write. Every speedup we ship cuts your infra bill while keeping your Quanton bill flat. Run in your own Kubernetes — or directly on VMs (EC2, GCE, Azure VMs, on-prem). Reserved and spot discounts stay yours.
$0.0009/GiB and drop to $0.0003/GiB above 1,000,000 GiB/month. Each rate applies only to usage within its band.- 100 GiB / month of Quanton-accelerated processing
- After the cap — automatic fallback to OSS Spark with Apache DataFusion Comet and Apache Gluten pre-installed, also free
- AI Spark Engineer included — works across every engine
- Community support via Slack
- Free on your laptop, free in a cluster — small data, no charge
- Unlimited Quanton-accelerated read/write — no throttling
- First 100 GiB / month free, carried over from the Free tier
- Six volume bands · from $0.0009 down to $0.0003 / GiB (see rate card)
- AI Spark Engineer included
- Community support via Slack
- Unlimited data volume for a single flat annual fee
- Unlock Onehouse Managed Lakehouse
- Dedicated support & CSM
- Custom contracts
- Volume discounts
Each band's rate applies only to the GiB that lands inside it. The first 100 GiB of every month is free; the next chunks unlock the next band's lower rate — automatically, no upgrade needed. Volumes measured in GiB (1,024 MiB), matching what Spark reports. Write is 2× the read rate.
Estimate your bill, side by side.
For a conservative estimate, we assume equal runtime—even though Quanton is 25% faster than Photon on TPC-DS 10 TB.
Models equal runtime for Quanton and Photon, with the same hardware and EC2 discount for Quanton and Photon Classic. OSS Spark uses 6.0× Quanton's runtime from the TPC-DS 10 TB benchmark. Serverless uses the same runtime and DBU estimate as Photon Classic, with infrastructure bundled into its rate. DBU rates: Classic $0.15, Serverless $0.35, Premium tier, US-East-1. Estimates only.
This estimate gives Quanton and Photon Classic equal runtime on the same hardware in your VPC — your EC2 discount applies to both. Serverless bundles compute at the higher $0.35/DBU rate. OSS Spark is free; this estimate uses 6.0× the runtime on the same cluster.
Click a preset above to see the worked breakdown for a real workload.
Compare execution times.
See TPC-DS 10 TB results and the wider benchmark suite on the Benchmarks page.
View benchmarks →See how the engines compare.
Compare deployment, execution, storage awareness, and AI capabilities across Quanton, Databricks, OSS Spark, Comet, and Gluten.
View the feature comparison →Questions a skeptical platform team would ask.
I run in my own VPC and already get an EC2 discount — what's the edge over Databricks Classic?
The calculator assumes equal runtime on the same hardware, so your EC2 discount applies equally to both. On the TPC-DS 10 TB preset, Quanton's platform fee is $5.38 versus $12.35 in Photon DBU fees — 56% lower. This estimate excludes Quanton's 25% performance advantage over Photon.
Why per-GiB instead of per-DBU or per-vCPU-hour?
Compute-time billing pays the vendor more when jobs run slowly. Every optimization we ship — better SIMD, smarter planning, native MERGE — would cut our own revenue if we billed by the hour. Per-GiB ties our income to the value delivered, not to inefficiency. The faster we make Spark, the better the deal you keep.
Does the rate change if I land on a different volume tier?
Yes — tier pricing is progressive. The GiB that lands in the 1–10 TiB band is billed at $0.0007; the next chunk in the 10–100 TiB band is billed at $0.0005; and so on. You don't fall off a cliff between tiers. Most single-run ETL workloads sit in the 1–10 TiB band; aggregate monthly volume often crosses into $0.0005 or $0.0004.
How does this compare to OSS Spark, Comet, or Gluten — all free?
Free engine, paid time. On TPC-DS 10 TB with the same 11-node cluster, OSS Spark takes 12,200s vs Quanton's 2,034s — 6.00× the EC2 hours. Comet and Gluten are 4.2–4.5× slower and OOM on q67/q93. The Quanton fee is smaller than the extra EC2 you'd burn waiting for OSS to finish — and that's before counting engineer time.
What if I want to walk away?
One config line points your orchestration back at OSS Spark, Comet, or Gluten. Same Scala / PySpark / SparkSQL jobs, no rewrites. Quanton ships as a Docker image and a Kubernetes operator that mirrors the Kubeflow SparkApplication spec. Your data never leaves your VPC; your jobs stay portable.
Is the AI Spark engineer extra?
No. Quanton AI lives in your Spark UI and is free — it works across Quanton, OSS Spark, Comet, and Gluten. Your Claude or OpenAI key lives in your browser; prompts and AI data never touch our servers.
Why GiB and not GB?
Spark UI reports read/write bytes in binary (1 GiB = 1,073,741,824 B). Billing on GB instead of GiB would silently change the fee by ~7%. We use the same unit Spark reports — no decoder ring required.
Bring a workload. We'll show you the diff.
Spin up Quanton in your own Kubernetes in under 10 minutes. Compare against your current Databricks bill in your own VPC.
