Comparisons
We sell Sigma and custom warehouse work, so read these knowing that. We still say where the other option is better, link every claim to the page we checked, and fix mistakes when a vendor tells us about them.
Sigma vs other BI tools
For teams on Snowflake, BigQuery, or Databricks choosing a BI layer.
Sigma vs Tableau: an honest comparison from a consultant who builds both
How Sigma and Tableau differ on warehouse queries, who can build reports, write-back, self-hosting, and pricing, with every claim linked to its source.
Sigma vs Omni: spreadsheet-first or model-first BI?
Sigma and Omni both query your warehouse live and both have spreadsheet views. The real difference is where the logic lives and who maintains it.
Sigma vs Hex: BI for the business or notebooks for the data team?
Hex is a SQL and Python notebook that publishes data apps. Sigma is a spreadsheet-style BI tool on your warehouse. Here is when each one is the right choice.
Sigma vs Metabase: when to pay for BI and when open source is enough
Metabase is open source with published low pricing. Sigma is a paid, spreadsheet-first tool for warehouse data. Here is what you get for the difference.
Sigma vs Power BI: which fits a company on Snowflake?
Power BI is cheap per seat and everywhere in Microsoft shops. Sigma queries Snowflake live in a spreadsheet. Here is how licensing, modeling, and write-back compare.
Sigma vs Looker: governed models or spreadsheet freedom?
Looker centers on a LookML model the data team owns. Sigma centers on a spreadsheet business users own. Here is how that plays out on Snowflake and BigQuery.
Custom warehouse vs packaged ecommerce reporting
For brands deciding between an off-the-shelf analytics app and a warehouse built around their own sources.
Triple Whale vs a custom data warehouse: which one does your brand need?
Triple Whale is attribution and dashboards for Shopify brands. A custom warehouse is one source of truth across every channel. Many brands end up running both.
Polar Analytics vs a custom data warehouse: managed Snowflake or your own?
Polar gives every customer a managed Snowflake database with prebuilt ecommerce metrics. Here is when that is enough and when you need models you own.
Lifetimely vs a custom data warehouse: profit and LTV for Shopify brands
Lifetimely gives Shopify brands daily P&L and LTV for $0 to $999 a month. Here is when that is all you need and when you have outgrown it.
Sellerboard vs a custom data warehouse: Amazon profit, or every channel?
Sellerboard is cheap, deep Amazon profit software. A warehouse puts Amazon next to Shopify, TikTok Shop, and wholesale in one model. Here is when each wins.
BeProfit vs a custom data warehouse: Shopify profit app or your own model?
BeProfit shows Shopify contribution profit for free to a few hundred dollars a month. Here is when that is enough and when you need a warehouse.
TrueProfit vs a custom data warehouse: live net profit or one model for every channel?
TrueProfit gives Shopify and TikTok Shop stores live net profit with many ad and supplier integrations. Here is when a warehouse makes more sense.
Supermetrics vs a custom data warehouse: a data pipe or a finished model?
Supermetrics moves marketing and store data into Sheets, Looker Studio, or a warehouse. It does not model profit. Here is how it fits with a custom build.
Improvado vs a custom data warehouse: enterprise marketing data or a commerce model?
Improvado loads 500+ marketing and commerce sources into your warehouse, with MMM and attribution add-ons. Here is what it covers and what still needs modeling.
Northbeam vs a custom data warehouse: attribution or the full P&L?
Northbeam is marketing measurement: a pixel, attribution, incrementality, and MMM. A warehouse is your business model. Most brands that need both run both.
Glew vs a custom data warehouse: hosted ecommerce BI or your own Snowflake?
Glew offers prebuilt ecommerce dashboards from $250 a month and a hosted warehouse with Looker on its Plus plan. Here is how that compares to owning the stack.
Saras Analytics (Daton, Pulse, iQ) vs a custom data warehouse
Saras sells ecommerce ELT (Daton), prebuilt dashboards (Pulse), and an AI analyst (iQ). Here is which part replaces a custom build and which part feeds one.
Klar vs a custom data warehouse: contribution margin out of the box or your own model?
Klar gives European DTC brands contribution margin, retention, and attribution from €200 a month. Here is when that fits and when you need your own warehouse.
Windsor.ai vs a custom data warehouse: cheap connectors or a finished model?
Windsor.ai moves data from 350+ sources into sheets, Looker Studio, or Snowflake from $19 a month. It does not model profit. Here is how it fits with a build.
Funnel vs a custom data warehouse: marketing data hub or commerce model?
Funnel collects and harmonizes data from hundreds of marketing sources, with MMM and attribution as an add-on. Here is where it ends and a warehouse model begins.
Peel vs a custom data warehouse: retention analytics or the whole business?
Peel is deep cohort and retention analytics for Shopify and subscription brands, with Snowflake access included. Here is when it is enough and when to build.
Daasity vs a custom data warehouse: packaged commerce models or built for you?
Daasity is the closest product to a custom build: managed pipelines and commerce models in your Snowflake or BigQuery. Here is how to choose between them.
Shopify Analytics vs a custom data warehouse: when built-in reports stop being enough
Shopify’s built-in analytics are free, real time, and better than ever. Here is what they cover and the point where brands need a warehouse instead.