Synopsis vs Sigma
The spreadsheet is the easy part.
Sigma makes a cloud warehouse feel like a spreadsheet, and business users love it for exactly that. But Sigma only works once the warehouse exists, your systems are loaded, and someone has modeled the data. Synopsis delivers that whole foundation — ingestion, warehouse, and modeling — plus the analysis on top, live in days.
What Sigma is
Sigma is a cloud analytics tool with a spreadsheet-like interface that runs live on your cloud data warehouse. It's genuinely good at what it does: people who are comfortable in Excel can explore billions of rows without writing SQL, and every calculation stays in the warehouse rather than being extracted. What Sigma is not is a warehouse or a pipeline. It doesn't connect to your source systems, load your data, or model and clean it for you — it assumes a populated, modeled warehouse is already there. To get to that starting line, teams typically stand up a warehouse (like Snowflake or BigQuery), an ingestion tool (like Fivetran), a transformation layer (like dbt), and the engineers to run it.
Sigma + the stack beneath it
A great spreadsheet interface, on top of everything you assemble to feed it.
- Sigma — the spreadsheet layer: powerful, but only as good as the warehouse under it
- A cloud warehouse — Snowflake, BigQuery, or Databricks for Sigma to query
- An ingestion tool — Fivetran, Airbyte, or custom pipelines to load your systems
- dbt + engineers — to model, clean, and join the raw data first
- Governance work — to define trusted metrics before analysts explore
- A data team — to build and maintain the whole foundation
- Timeline — a multi-month build before the first spreadsheet points at trustworthy data
Synopsis
One platform: the warehouse, the pipeline, and the analysis on top, live in days.
- The warehouse itself — open, queryable, and yours
- Ingestion built in — your systems connect, data lands clean, no pipelines to babysit
- Modeling done for you — raw events become clean, joined entities automatically
- Analysis included — dashboards from a single prompt, and your data live in Excel and Sheets
- Built-in alerts — the platform watches your data for you
- No data team required — we configure it with you
- AI-ready from day one — your AI tools query it over MCP
Side by side
Sigma vs Synopsis, capability by capability.
| Capability | Sigma | Synopsis |
|---|---|---|
| Cloud warehouse & fast SQL | ○ | ● |
| Connects to your business systems | ○ | ● |
| Data modeled, cleaned & joined for you | ◐ | ● |
| Ask across every system in plain English | ◐ | ● |
| Dashboards & BI included | ● | ● |
| Alerting on your own data | ◐ | ● |
| Metrics defined once, governed everywhere | ◐ | ● |
| Live in days without a data team | ○ | ● |
| One vendor for the whole pipeline | ○ | ● |
| Query-ready for your AI tools (MCP) | ○ | ● |
| Spreadsheet-native analysis directly on the warehouse | ● | ◐ |
● Included ◐ Possible with effort or extra tools ○ Not available
An honest take
Where Sigma is the stronger choice.
A true spreadsheet experience on live data
If your team lives in Excel and wants that exact interaction — cells, formulas, pivots — over warehouse-scale data without extracts, Sigma is purpose-built for it. That familiar, no-extract spreadsheet feel is its home turf, and it's excellent.
You already have a modeled warehouse
If your warehouse is already stood up, loaded, and cleanly modeled, Sigma is a strong analysis layer to put on top of it. Synopsis is aimed at the far more common case where that foundation doesn't exist yet.
Deep, ad-hoc self-serve exploration
Sigma is built for business users to slice, pivot, and calculate freely without waiting on an analyst. If open-ended spreadsheet exploration by non-technical users is the main job, that's where Sigma shines.
The bottom line
Sigma is a great way to explore data that's already sitting in a well-built warehouse, and if you have that foundation, its spreadsheet interface is hard to beat. But Sigma is the top layer — it doesn't ingest your systems, build the warehouse, or model your data. Synopsis delivers all of that as one platform, with analysis on top, and your data still open and queryable. You get the answers in days instead of assembling the stack that Sigma needs underneath it.
Questions
Is Synopsis a Sigma alternative?
They solve overlapping problems from opposite ends. Sigma is an analysis layer that needs a warehouse and pipeline underneath it; Synopsis includes the warehouse, ingestion, and modeling and adds analysis on top. If you're weighing 'Sigma plus a full stack' against 'one platform,' then yes — Synopsis is a real alternative.
Can Synopsis replace Sigma?
For most teams, Synopsis replaces both Sigma and the stack it sits on. You get dashboards and prompt-driven analysis, plus your live data in Excel and Sheets. If your team specifically wants Sigma's full spreadsheet-cell interaction on the warehouse, that particular experience is Sigma's specialty — but Synopsis covers the analysis most businesses actually need.
Does Sigma include a data warehouse?
No. Sigma runs on top of your cloud data warehouse, such as Snowflake or BigQuery, and assumes it's already populated and modeled. You bring the warehouse, ingestion, and modeling. Synopsis includes all three, so there's nothing to assemble underneath.
How fast can we be live compared with a Sigma stack?
A Sigma deployment is only as fast as the warehouse and pipeline beneath it, which is usually a multi-month project. Synopsis connects your systems and delivers trustworthy, modeled data with dashboards on top in days, with no data team required on your side.
See it on your own data.
Bring a question you've been trying to answer with Sigma and the tools around it.
