Warehouse Cost Translator

1. Extract your BigQuery job history

This query returns hourly aggregates only: job counts, bytes billed and slot-milliseconds. No query text, no table or dataset names, no user identities. Everything below runs in your browser and nothing you paste is transmitted.

-- Finitizer Slot Advisor extract: hourly aggregates only.
-- Returns no query text, no table names, and no user identities.
-- Slot time is booked to the hour it was used (JOBS_TIMELINE), so a job that
-- runs for three hours counts in each of them. Bytes and job counts come from
-- JOBS, by the hour each job was created. Script parents are left out, so a
-- script's statements are counted once.
WITH slot_time AS (
  SELECT
    TIMESTAMP_TRUNC(period_start, HOUR)                      AS hour,
    SUM(period_slot_ms)                                      AS slot_ms
  FROM `region-us`.INFORMATION_SCHEMA.JOBS_TIMELINE_BY_PROJECT
  WHERE job_creation_time >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 31 DAY)
    AND period_start >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 30 DAY)
    AND job_type = 'QUERY'
    AND (statement_type != 'SCRIPT' OR statement_type IS NULL)
  GROUP BY hour
),
job_totals AS (
  SELECT
    TIMESTAMP_TRUNC(creation_time, HOUR)                     AS hour,
    COUNT(*)                                                 AS jobs,
    SUM(total_bytes_billed)                                  AS bytes_billed,
    APPROX_QUANTILES(
      SAFE_DIVIDE(
        total_slot_ms,
        NULLIF(TIMESTAMP_DIFF(end_time, start_time, MILLISECOND), 0)
      ), 100
    )[OFFSET(95)]                                            AS p95_job_avg_slots
  FROM `region-us`.INFORMATION_SCHEMA.JOBS_BY_PROJECT
  WHERE creation_time >= TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 30 DAY)
    AND job_type = 'QUERY'
    AND (statement_type != 'SCRIPT' OR statement_type IS NULL)
    AND total_slot_ms IS NOT NULL
  GROUP BY hour
)
SELECT
  COALESCE(j.hour, s.hour)                                   AS hour,
  IFNULL(j.jobs, 0)                                          AS jobs,
  IFNULL(j.bytes_billed, 0)                                  AS bytes_billed,
  IFNULL(s.slot_ms, 0)                                       AS slot_ms,
  j.p95_job_avg_slots                                        AS p95_job_avg_slots
FROM job_totals j
FULL OUTER JOIN slot_time s ON s.hour = j.hour
ORDER BY 1;

The bridge: the assumption doing the work

BigQuery sells slots, Snowflake sells credits, Databricks sells DBUs, and no vendor publishes a conversion between them. Any tool that translates between these platforms is making an assumption; this one lets you move it and see whether the answer survives. If the decision flips inside the plausible band, the honest conclusion is that a rate card cannot settle it and you need a proof of concept.

Your rates

Both start at list price: Snowflake’s Enterprise credit in AWS US East, and Databricks’ rate card for the cloud and plan picked. Most contracts are not list, so enter yours.