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Warehouse UX · open engine · your AWS

A Snowflake-grade warehouse. On stock Spark. In your account.

Warehouse UX on stock Apache Spark. Metered by the second. In your own AWS account.

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The Flashpoint DB worksheet: SQL editor beside a results grid, with a running warehouse shown in the header.
worksheet: SQL on the left, results on the right, compute metered underneath
~30s
cold start in our tests
in-VPC
compute, state and results stay in your account
per-second
metering, no minimum, $0 compute when suspended
MIT
read the code, own the deployment
01What changes

You already run Spark. This gives it a warehouse face.

The engine stays Apache Spark. What changes is the layer your team works in.

Spark today

  • Notebooks stapled to a long-lived cluster
  • Job logs instead of a query profile
  • A cluster bill you cannot attribute per query

Spark with Flashpoint

  • A worksheet, and warehouses you create, suspend and resize
  • An operator-tree query profile for every query
  • Per-second metering, and a cost center beside the AWS bill
02What it costs

An hour of the smallest size.

Per compute-second, and only while a warehouse runs. A suspended warehouse bills nothing.

Snowflake $2.00 / hour 1 credit/hour at list, 60-second minimum each start
Flashpoint DB $0.08 / hour one executor on the rate card, no minimum; the driver meters separately
03Your VPC

Data never leaves your account.

Gateway, driver, executors and results all run inside your VPC, on your IAM and your S3, reached over an endpoint you open.

Data stays in your VPC YOUR AWS ACCOUNT · VPC notebook SQL client gRPC Gateway stateless REST ECS Fargate Driver · on-demand Executors · spot S3 · results
04The proof

Where the query spent its time.

Not a job log. The operators ranked by duration, the slow one first.

HashAggregate 4.8 s
BroadcastHashJoin 3.0 s
Scan parquet · orders 318 ms
Scan parquet · customers 301 ms
Exchange 155 ms
AdaptiveSparkPlan 29 ms
  • Find the slow step, not the slow job
  • Share any query as a link
  • See what the query cost
05The bill

You pay for the seconds it runs.

Metered per compute-second while a warehouse is up. Suspended warehouses bill nothing.

You pay only while it runs $0.08/h $0 running suspended · $0 running time
  • Per compute-second, no minimum
  • Suspended is $0 compute
  • Live meters beside the AWS bill
06Lifecycle

Create it, run it, suspend it.

A warehouse starts on demand and stops when idle. You never manage a node.

Warehouse lifecycle Create tens of seconds on AWS Run metered per compute-second Suspend $0 compute while idle resume on activity
07Questions

Straight answers.

How close is it to Snowflake?

It copies the shape of the product: the warehouse, the worksheet, the query profile, the per-second billing. Your data stays in open formats, so there is nothing to migrate back out of.

What does it cost?

Per compute-second on a running warehouse. Suspended warehouses bill nothing. Sizes run on a published rate card from $0.08/h for one executor. There are no credits and no per-seat fees.

Where does my data live?

In your AWS account: Iceberg tables and Parquet results on your S3, catalog in your Glue, state in your DynamoDB. Nothing leaves the account.

Can I use it from a notebook or pandas?

Yes, anything that speaks Spark Connect can attach to a warehouse's gRPC endpoint. The REST gateway is there for SQL and lifecycle calls.

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