What is Stripe Sigma?
Stripe Sigma is a SQL environment inside your Stripe account. It gives analysts direct access to raw data - charges, subscriptions, customers, invoices, refunds - and lets them write custom queries to answer almost anything. You can save queries, export results and schedule reports.
A query for monthly revenue looks like this:
SELECT DATE_TRUNC('month', created) AS month,
SUM(amount) / 100.0 AS revenue
FROM charges
WHERE status = 'succeeded'
GROUP BY 1
ORDER BY 1 DESCFor a team with a dedicated analyst, that is a genuinely powerful environment. For everyone else the workflow is slow: write SQL, run it, inspect the table, turn it into a chart, save it. There is no pre-built SaaS metrics layer, so you derive MRR, churn and LTV from raw events yourself. And because Sigma is Stripe-only, cross-referencing anything else means manual exports.
For a deeper look at Sigma on its own terms - features, pricing tiers and limitations - see What Is Stripe Sigma?
How does Chartsy differ from Stripe Sigma?
Chartsy removes the query step. You ask a question in plain English - “what is my MRR for the last 12 months?”, “show churn by country”, “which plans are growing fastest?” - and Chartsy interprets it, finds the right Stripe data, picks a chart type and renders it.
The difference is where the work happens. Sigma hands you the raw tables and expects you to build the metrics layer. Chartsy ships that layer already built: MRR, churn rate, LTV and net revenue retention are calculated from your billing records without anyone writing a definition for them.
Stripe Dashboard vs Sigma vs Chartsy
Most teams on Stripe already use two tools: the Dashboard for quick monitoring and Sigma for deep analysis. They sit at opposite ends, and the gap between them is where most everyday questions fall.
| Capability | Stripe Dashboard | Stripe Sigma | Chartsy |
|---|---|---|---|
| Data exploration | Fixed reports | Full SQL access | Ask any question, instant charts |
| Ease of use | Easy for basics | Requires SQL | No SQL, no setup |
| Pre-built SaaS metrics | Partial | None - you derive them | MRR, churn, LTV, NRR built in |
| Time to an answer | Seconds, if built in | Minutes to hours | Seconds |
| Pricing model | Included | Per row queried | Fixed monthly tier |
| Best for | Daily monitoring | Data teams and analysts | Founders and operators |
What does Stripe Sigma actually cost?
Sigma is billed per row queried rather than as a flat fee, which makes it unusually hard to budget for. Two variables drive the bill: how much Stripe data you hold, and how often you query it. Both grow over time, so the same reporting habit costs more every quarter.
The practical consequence is a behaviour change rather than a line item. Teams on per-row pricing tend to query less often, which is the opposite of what you want from an analytics tool. A fixed monthly tier removes that hesitation: within your plan's query allowance, the twentieth question in a day costs the same as the first.
Sigma also has a hidden cost that never appears on an invoice - analyst time. Every recurring report is a query somebody wrote, and somebody has to maintain it when your plans, metadata or pricing change.
When is Stripe Sigma the better choice?
Sigma is the right tool in three situations, and it is worth being straight about them:
- You have an analyst already. If someone on the team writes SQL comfortably, Sigma gives them unrestricted access to every field Stripe stores. No abstraction layer will ever be as flexible as the raw tables.
- Your questions are genuinely bespoke. Standard SaaS metrics are a solved problem. If your analysis depends on logic specific to your business that no tool ships by default, SQL is the honest answer.
- You need to join Stripe against other data. If Stripe records have to be combined with product or warehouse tables in one query, that is a SQL job.
Outside those cases, the SQL requirement is a tax rather than a feature. If the questions you ask are the ones every subscription business asks - what is my MRR, which plans churn, where is expansion coming from - paying in analyst hours to rebuild answers that already exist is hard to justify.
Frequently asked questions
What is Stripe Sigma used for?
Sigma runs custom SQL queries directly against your raw Stripe data - charges, subscriptions, customers, invoices and refunds - for analysis that goes beyond the Dashboard’s built-in reports. Teams typically use it for ad hoc revenue queries, custom cohort breakdowns and scheduled exports pulled straight from Stripe’s underlying tables.
Do you need to know SQL to use Stripe Sigma?
Yes. Sigma is a SQL query environment, with no plain-English or point-and-click way to pull data. Every report starts as a query written against Stripe’s Sigma schema, which is the main barrier for founders and operators without a SQL background.
How much does Stripe Sigma cost?
Sigma is billed per row queried rather than as a flat subscription, so the cost scales with both how much data you hold and how often you query it. That makes it unpredictable: the same question asked weekly against a growing dataset costs more every month. Chartsy charges a fixed price for your plan tier - set by the website events you track, not by how much you query - so asking the same question every week never moves the bill.
Is Stripe Sigma worth the extra cost?
It depends on whether someone on your team already writes SQL. With a data analyst in-house, Sigma’s flexibility can justify the cost, because it gives direct access to every field in your Stripe data. Without one, the cost is harder to justify, since every report still has to be written, maintained and turned into a chart by hand.
When is Stripe Sigma the better choice?
When you have an analyst who needs unrestricted SQL access to raw Stripe objects, when your questions are genuinely bespoke rather than standard SaaS metrics, or when you need to join Stripe data against your own tables in a warehouse. Sigma’s flexibility is real - it simply comes with a SQL requirement.
Is Chartsy a Stripe Sigma alternative?
For most teams, yes. Sigma requires SQL to answer questions; Chartsy lets you ask in plain English and returns a chart instantly, with MRR, churn, LTV and other SaaS metrics already calculated. If you do not have an analyst writing queries, Chartsy gets you the same answers without the SQL.
How fresh is the data in Stripe Sigma?
Sigma is not real-time - Stripe’s own documentation notes a processing delay before new events appear in query results, which matters if you are checking today’s numbers rather than doing historical analysis. Chartsy’s synced data follows a similar near-real-time model, so if freshness is a deciding factor it is worth checking the current sync interval in either tool’s docs rather than assuming.
Does Chartsy replace Stripe?
No. Chartsy connects to Stripe and reads your data to provide analytics. You keep using Stripe to process payments; Chartsy is the interpretation layer on top of it.
Does Chartsy work beyond Stripe?
Yes. Chartsy also supports Paddle Billing and Paddle Classic, so you can analyse subscription revenue across multiple processors in one place. Sigma is Stripe-only by design, so cross-referencing anything outside Stripe means manual exports.
