Stripe MRR SQL Query: Sigma, Data Pipeline & Fivetran

Quick answer

Current MRR per currency, straight from Stripe’s MRR change log. Paste it into the Sigma editor.

-- Stripe Sigma (Trino)
-- Current MRR per currency, in major units (dollars, euros)
select
  currency,
  sum(mrr_change) / 100.0 as mrr
from subscription_item_change_events_v2_beta
group by currency
order by mrr desc

Every row in subscription_item_change_events_v2_beta is a change to one subscription item’s MRR: a start, an end, an upgrade or a downgrade. Add up every change and you get MRR today.

Schema assumptions

Source	Tables used	Notes
Stripe Sigma	subscription_item_change_events_v2_beta (event_timestamp, local_event_timestamp, currency, mrr_change, quantity_change, event_type, customer_id, subscription_id, subscription_item_id, product_id, price_id), products (id, name), customers (id, email)	mrr_change is in minor units. event_type is ACTIVE_START, ACTIVE_END, ACTIVE_UPGRADE, ACTIVE_DOWNGRADE, ACTIVE_QUANTITY_INCREASE or ACTIVE_QUANTITY_DECREASE.
Stripe Data Pipeline	Same tables under schema STRIPE (test data in STRIPE_TESTMODE)	Snowflake, Redshift, BigQuery or Databricks. Amounts in minor units.
Fivetran	subscription_history (id, status, _fivetran_active), invoice (id, status, created), invoice_line_item (invoice_id, subscription_id, subscription_item_id, price_id, amount, currency, type, proration), price (id, recurring_interval, recurring_interval_count)	No change-events table. subscription_history exists on connections created after 1 Feb 2022; older ones have subscription.
Airbyte	subscriptions, subscription_items, invoices, invoice_line_items	API-shaped: customer and subscription instead of *_id, Unix-epoch integer timestamps, price and period as JSON.

Copy-ready SQL

1. MRR by month

Ending MRR for each month in which something changed. Change: nothing, except dividing by 1 instead of 100 for zero-decimal currencies.

-- Stripe Sigma (Trino)
with monthly as (
  select
    date_trunc('month', local_event_timestamp) as month,
    currency,
    sum(mrr_change) as mrr_change
  from subscription_item_change_events_v2_beta
  group by 1, 2
)
select
  month,
  currency,
  sum(mrr_change) over (partition by currency order by month) / 100.0 as ending_mrr
from monthly
order by month desc, currency

Example output (made-up data):

month	currency	ending_mrr
2026-09-01	usd	18420.00
2026-08-01	usd	17150.00
2026-07-01	usd	16380.00

2. New, expansion, contraction and churned MRR by month

The MRR bridge investors ask for. This version classifies each subscription item’s event. Stripe’s full template (Sigma sidebar → Subscriptions) classifies per customer instead, so a plan switch shows as expansion there rather than churn plus new here.

-- Stripe Sigma (Trino)
select
  date_trunc('month', local_event_timestamp) as month,
  currency,
  sum(case when event_type = 'ACTIVE_START' then mrr_change else 0 end) / 100.0 as new_mrr,
  sum(case when event_type = 'ACTIVE_UPGRADE' then mrr_change else 0 end) / 100.0 as expansion_mrr,
  sum(case when event_type = 'ACTIVE_DOWNGRADE' then mrr_change else 0 end) / 100.0 as contraction_mrr,
  sum(case when event_type = 'ACTIVE_END' then mrr_change else 0 end) / 100.0 as churned_mrr,
  sum(mrr_change) / 100.0 as net_new_mrr
from subscription_item_change_events_v2_beta
group by 1, 2
order by 1 desc, 2

Example output (made-up data):

month	currency	new_mrr	expansion_mrr	contraction_mrr	churned_mrr	net_new_mrr
2026-09-01	usd	1490.00	380.00	-120.00	-480.00	1270.00
2026-08-01	usd	1210.00	150.00	-60.00	-530.00	770.00

3. MRR by product

Which product carries the business. Change: nothing.

-- Stripe Sigma (Trino)
select
  p.name as product,
  e.currency,
  sum(e.mrr_change) / 100.0 as mrr
from subscription_item_change_events_v2_beta e
join products p on p.id = e.product_id
group by 1, 2
having sum(e.mrr_change) > 0
order by mrr desc

Example output (made-up data):

product	currency	mrr
Pro	usd	12600.00
Team	usd	5820.00

4. Top customers by MRR

Your biggest accounts, and how concentrated revenue is. Change: the limit.

-- Stripe Sigma (Trino)
select
  c.email,
  e.currency,
  sum(e.mrr_change) / 100.0 as mrr
from subscription_item_change_events_v2_beta e
join customers c on c.id = e.customer_id
group by 1, 2
having sum(e.mrr_change) > 0
order by mrr desc
limit 20

Example output (made-up data):

email	currency	mrr
ops@acme.example	usd	990.00
finance@globex.example	usd	490.00

5. MRR by month in Stripe Data Pipeline (Snowflake)

Same logic as query 1, run in your warehouse. Change: stripe to your Data Pipeline database and schema, for example stripe_db.stripe.

-- Snowflake (Stripe Data Pipeline)
with monthly as (
  select
    date_trunc('month', local_event_timestamp) as month,
    currency,
    sum(mrr_change) as mrr_change
  from stripe.subscription_item_change_events_v2_beta
  group by 1, 2
)
select
  month,
  currency,
  sum(mrr_change) over (partition by currency order by month) / 100 as ending_mrr
from monthly
order by month desc, currency;

6. Current MRR from Fivetran tables (Postgres)

Fivetran has no MRR change log, so build MRR from what each active subscription last paid for: the latest paid, non-proration subscription line per subscription item, normalised to a month by the price interval. Change: the stripe schema name.

-- PostgreSQL (Fivetran Stripe schema "stripe")
with active as (
  select id
  from stripe.subscription_history
  where _fivetran_active
    and status in ('active', 'past_due')
),
latest_line as (
  select distinct on (li.subscription_item_id)
    li.currency, li.amount, p.recurring_interval, p.recurring_interval_count
  from stripe.invoice_line_item li
  join stripe.invoice i on i.id = li.invoice_id
  join stripe.price p on p.id = li.price_id
  join active a on a.id = li.subscription_id
  where li.type = 'subscription'
    and not li.proration
    and i.status = 'paid'
  order by li.subscription_item_id, i.created desc
)
select
  currency,
  round(sum(
    amount * case recurring_interval
      when 'month' then 1.0
      when 'year' then 1.0 / 12
      when 'week' then 52.0 / 12
      when 'day' then 365.0 / 12
    end / recurring_interval_count
  ) / 100, 2) as mrr
from latest_line
group by currency
order by mrr desc;

Example output (made-up data):

currency	mrr
usd	18310.42
eur	2150.00

This runs high if you discount at the invoice level, because line amount is before invoice coupons. On Snowflake or BigQuery, replace distinct on with qualify row_number() over (partition by li.subscription_item_id order by i.created desc) = 1.