--- title: "OWOX Data Marts vs Supermetrics vs Airbyte compared" canonical: "https://www.owox.com/blog/articles/owox-vs-supermetrics-vs-airbyte" updated: "2026-10-07" --- # OWOX Data Marts vs Supermetrics vs Airbyte: which one fits your marketing data The three tools are not interchangeable. Supermetrics is a managed service that delivers marketing data to reporting tools. Airbyte is a general data movement platform for engineers. OWOX Data Marts loads marketing data into your own data warehouse and governs what business users and AI read from it. [Data Integration](/blog/topics/data-integration) · Updated October 1, 2026 · [Ievgen Krasovytskyi](/team/ievgen-krasovytskyi) · 7 min read ![OWOX Data Marts vs Supermetrics vs Airbyte: which one fits your marketing data](https://cdn.owox.ai/www/webflow/6985fc273ee567a937e4f068_OWOX-Data-Marts-vs.-Supermetrics-vs.-Airbyte_-Which-is-Right-for-Analysts.png/public) If you are choosing between Supermetrics, Airbyte and OWOX Data Marts, the first thing to know is that **they are not three versions of the same tool**. Each was built for a different job, so the useful question is which job you have. This comparison was checked against each vendor’s own pricing and documentation pages in October 2026. Plans and prices change, so the vendor claims below link to the page they came from and carry no price figures. ## The short version * **Supermetrics** is a managed service that pulls marketing data and delivers it to the reporting tool you already use. You pay for convenience. * **Airbyte** is a general data movement platform, open source at its core, built for data engineers who move many kinds of data between many systems. * **OWOX Data Marts** loads marketing data into **your own data warehouse**, lets an analyst define governed data marts on top of it in SQL, and publishes those to Google Sheets, dashboards and AI assistants. It is [open source](https://www.owox.com/blog/articles/free-open-source-connectors-for-analysts) and can also run as OWOX Cloud. ## What each tool is built for ### Supermetrics: marketing data, delivered to a reporting tool Supermetrics connects to marketing platforms and sends the data to a destination. Its [pricing page](https://supermetrics.com/pricing) lists Google Sheets, Looker Studio, Microsoft Excel and Power BI as core destinations, alongside AI assistants, and names four plans: Starter, Growth, Pro and Enterprise. The same page says what the price depends on: the number of **data sources**, the **destinations**, the **users** and the **accounts per data source**. Data warehouse destinations such as BigQuery and Snowflake are listed under the Enterprise plan. There is a 14-day free trial. It fits a team that wants a report in a spreadsheet this week, has no data warehouse and does not plan to keep the raw data. ### Airbyte: data movement for engineers Airbyte moves data from sources to destinations across a much wider range than marketing. Its [pricing page](https://airbyte.com/pricing) lists Airbyte Core, the open-source offering you host yourself, and cloud plans priced by volume through credits or, on the higher plans, by capacity. Running it yourself is an engineering task. The [quickstart](https://docs.airbyte.com/platform/using-airbyte/getting-started/oss-quickstart) asks for Docker Desktop and Airbyte’s `abctl` command-line tool, and recommends four or more CPUs and at least 8 GB of memory. Airbyte is aimed at warehouses and lakes, not spreadsheets. Its own [Google Sheets destination page](https://docs.airbyte.com/integrations/destinations/google-sheets) classifies the connector at the Marketplace support level and says Google Sheets should only be used for small, non-production use cases. It fits a data engineering team that needs one platform for product, finance and marketing data together and is ready to operate it. ### OWOX Data Marts: marketing data in your warehouse, governed for the people who read it OWOX Data Marts starts where the other two stop. Loading the data is the first step, not the product. 1. **[Open-source](https://github.com/OWOX/owox-data-marts) connectors load into your own data warehouse.** Each source is a data mart of the Connector type, with a manual backfill and scheduled runs. The same connector can land in BigQuery, Snowflake, Databricks, AWS Athena or AWS Redshift. ![OWOX Data Marts list filtered to Facebook Ads, showing connector data marts for the same source loading into BigQuery, Snowflake, AWS Athena and AWS Redshift – one connector, the data warehouse you choose](https://cdn.owox.ai/www/content-marketing-article/owox-vs-supermetrics-vs-airbyte/screens/1.png/public) 2. **Analysts define data marts in SQL.** OWOX does not transform data for you. The analyst writes the query, and OWOX schedules, [governs](https://www.owox.com/features/data-mart-management) and publishes it. In OWOX’s demo e-commerce project, one data mart unifies seven ad platforms into one row per date, source and campaign, and every block links to the connector it reads. ![Data Setup of the Unified Ad Spend data mart in OWOX Data Marts, showing the SQL input source with the first block reading the Facebook Ads connector table and mapping spend, clicks and impressions to shared columns](https://cdn.owox.ai/www/content-marketing-article/owox-vs-supermetrics-vs-airbyte/screens/2.png/public) 3. **The same data mart is published everywhere people read.** [Google Sheets](https://www.owox.com/data-destinations/google-sheets), [Looker Studio](https://www.owox.com/data-destinations/looker-studio), Slack and email are destinations of one governed data mart, so the number in the sheet is the number in the dashboard. ![Destinations in OWOX Data Marts listing Google Sheets, Slack, Email and Looker Studio – one governed data mart delivered to every place the team already reads](https://cdn.owox.ai/www/content-marketing-article/owox-vs-supermetrics-vs-airbyte/screens/3.png/public) 4. **AI assistants answer from the governed data marts.** Through [OWOX MCP](https://www.owox.com/features/mcp), Claude reads the data marts and the joins the analyst defined instead of guessing from raw tables. Here it answers “Which campaigns are scaling spend without a matching lift in orders?” against the demo project: ![Claude answering through OWOX MCP with a bar chart of year-to-date spend growth against conversion growth by channel and campaign, plus a written summary naming the two campaigns that scale spend without matching conversions](https://cdn.owox.ai/www/content-marketing-article/owox-vs-supermetrics-vs-airbyte/screens/4.png/public) It fits a team with an analyst who owns the numbers and business users who want to read them, in Sheets or by asking, without waiting for a new export each time. ## The Turning Point OWOX Data Marts See your first report built in real time. _15 minutes._ 1. Connect your data warehouse 2. Pick your metrics 3. Get a live Google Sheets report In the time it takes to write a ticket. Then imagine never writing that ticket again. [Book a Demo](/book-a-call) We'll use your actual use case ## Side by side **Built for** * Supermetrics: marketers who need data in a reporting tool * Airbyte: data engineers moving any data * OWOX Data Marts: analysts who hand governed data to business users **Where the data lives** * Supermetrics: delivered to the destination you pay for * Airbyte: the warehouse or lake you load into * OWOX Data Marts: your own data warehouse **Open source** * Supermetrics: managed service * Airbyte: Airbyte Core is open source * OWOX Data Marts: yes, [on GitHub](https://github.com/OWOX/owox-data-marts) **How you pay** * Supermetrics: per plan: data sources, destinations, users, accounts * Airbyte: self-hosted Core, or cloud plans by volume or capacity * OWOX Data Marts: free when you run it yourself; OWOX Cloud has its own [pricing](https://www.owox.com/pricing) **Running it yourself** * Supermetrics: managed service * Airbyte: Docker and `abctl`, 4+ CPUs and 8 GB recommended * OWOX Data Marts: Node.js and the OWOX CLI (`owox serve`) **Google Sheets** * Supermetrics: a core destination * Airbyte: Marketplace connector, small non-production use * OWOX Data Marts: a destination of a data mart, by report or extension **Where metrics are defined** * Supermetrics: in each report you build * Airbyte: in whatever you build downstream * OWOX Data Marts: once, by the analyst, in the data mart **AI answers** * Supermetrics: listed as a destination * Airbyte: not its job * OWOX Data Marts: from governed data marts through OWOX MCP The Supermetrics and Airbyte lines come from the pages linked above. Where a vendor’s page says nothing, the line describes scope, not a shortcoming. ## The differences that matter after month one ### Where your history lives A tool that delivers data straight into a report keeps no history of its own for you: when a platform changes its API or a sheet is overwritten, the old numbers go with it. Data loaded into your own data warehouse stays there, and a Google Sheets file has a hard ceiling of 10 million cells that a data warehouse does not. This is the reason OWOX Data Marts has no direct ad-platform-to-sheet connector. The route is source, then data warehouse, then Google Sheets as a destination. The [Facebook Ads → Google Sheets guide](https://www.owox.com/blog/articles/free-facebook-ads-connector-to-google-sheets) walks through it. ### Who decides what “spend” means Loading data does not unify it. Reddit reports spend in micros, X Ads exposes no conversion fields, and Facebook returns conversions as a JSON array. Somebody has to settle those differences. With a report-delivery tool, they are settled in each report, again and again. With a data movement platform, they are settled in whatever you build afterwards. In OWOX Data Marts they are settled once, in the data mart’s SQL, where they can be read and reviewed. The [unified ad report guide](https://www.owox.com/blog/articles/unified-ad-report-google-sheets) shows that query. ### What an AI assistant is allowed to read Pointing an assistant at raw warehouse tables gets you a plausible number with an invented join. Pointing it at published data marts gets you the analyst’s join and the query behind the answer, logged in Run History. MCP is the interface here; the guarantee is the governed data mart. More in [governed MCP analytics](https://www.owox.com/blog/articles/governed-mcp-analytics). ## How to choose * **Choose Supermetrics** if you need marketing data in a spreadsheet or a dashboard quickly, have no data warehouse, and accept paying per source and destination for a managed service. * **Choose Airbyte** if you have data engineers, the data goes far beyond marketing, and you want one platform to move all of it into a warehouse or lake. * **Choose OWOX Data Marts** if you want marketing data in your own data warehouse, an analyst in control of the definitions, and business users reading the same governed numbers in Sheets, dashboards and AI assistants. They can also coexist. A team already loading data with another tool can still define and publish data marts on top of the same warehouse tables. ## Try OWOX Data Marts * **OWOX Cloud:** [sign up](https://www.owox.com/app-signup) and connect your first source. * **Self-managed:** install Node.js 22.22.0 or later, run `npm install -g owox`, then `owox serve`. * **Read the code:** the project is on [GitHub](https://github.com/OWOX/owox-data-marts). Leave a ⭐ star if it is useful. ## Your New Normal Turn your data into decisions. Governed data marts give you the clean foundation ML needs to actually work. * No AI hallucinations * Analyst-governed definitions * Every number traces to SQL [Get started free](https://www.owox.com/app-signup) ## FAQ ## Frequently Asked Questions Can I use OWOX Data Marts alongside Supermetrics or Airbyte? Yes. If another tool already loads data into your data warehouse, you can still define data marts in SQL on top of those tables in OWOX Data Marts and publish them to Google Sheets, Looker Studio, Slack or AI assistants. Do I need coding skills to use OWOX Data Marts or Airbyte? Connecting a source in OWOX Data Marts is point and click. Defining a data mart takes SQL, written by an analyst; business users then read the result without SQL. Running Airbyte yourself is an engineering task: its quickstart asks for Docker Desktop and the abctl command-line tool. Can I send data to Google Sheets with Supermetrics, Airbyte and OWOX Data Marts? Supermetrics lists Google Sheets as a core destination. Airbyte has a Google Sheets destination at the Marketplace support level, which its documentation recommends only for small, non-production use. In OWOX Data Marts, Google Sheets is a destination of a data mart that lives in your data warehouse, reached by a report or by the OWOX Data Marts extension. How does pricing differ between Supermetrics, Airbyte and OWOX Data Marts? Supermetrics prices its plans by data sources, destinations, users and accounts per data source. Airbyte offers the open-source Airbyte Core to host yourself and cloud plans priced by volume or capacity. OWOX Data Marts is free and open source when you run it yourself, and OWOX Cloud has its own pricing page. Check each vendor’s pricing page for current figures. What is the key difference between Supermetrics, Airbyte and OWOX Data Marts? They do different jobs. Supermetrics delivers marketing data to a reporting tool as a managed service. Airbyte moves any kind of data between systems for engineering teams. OWOX Data Marts loads marketing data into your own data warehouse and governs the data marts that business users and AI assistants read from it. ## Who wrote this ![Ievgen Krasovytskyi](https://cdn.owox.ai/www/webflow/68404586b341508a789a4aa5_.png/public) [Ievgen Krasovytskyi](/team/ievgen-krasovytskyi) · Head of Marketing Ievgen Krasovytskyi is the Head of Marketing at OWOX, leading strategy across content, SEO, product marketing, and AI-powered automation. With deep expertise in analytics infrastructure, data warehouses, and marketing technology, he builds systems that connect marketing performance to business outcomes. Ievgen writes about SaaS growth, analytics workflows, and the future of AI in marketing operations. [LinkedIn](https://www.linkedin.com/in/ievgen-krasovytskyi-a38a1253/) · [All articles](/team/ievgen-krasovytskyi) [Data Integration](/blog/topics/data-integration) ## Related articles [Google BigQuery · Build GA4 BigQuery Dashboard in Looker Studio in 2025 · February 24, 2025](/blog/articles/ga4-bigquery-export-building-looker-studio-dashboard) [Data Integration · Free Facebook Ads to BigQuery connector by OWOX · October 1, 2026](/blog/articles/free-facebook-ads-to-bigquery-connector) [Data Integration · Free TikTok Ads to BigQuery connector by OWOX · October 1, 2026](/blog/articles/free-tiktok-ads-to-bigquery-connector) [See all articles →](/blog/articles) ## Links Pages this page links to, on this site and on docs.owox.com. Where the page has a Markdown twin, its address follows the link. - [Data Integration](https://www.owox.com/blog/topics/data-integration) — /blog/topics/data-integration.md - [Ievgen Krasovytskyi](https://www.owox.com/team/ievgen-krasovytskyi) — /team/ievgen-krasovytskyi.md - [open source](https://www.owox.com/blog/articles/free-open-source-connectors-for-analysts) — /blog/articles/free-open-source-connectors-for-analysts.md - [governs](https://www.owox.com/features/data-mart-management) — /features/data-mart-management.md - [Google Sheets](https://www.owox.com/data-destinations/google-sheets) — /data-destinations/google-sheets.md - [Looker Studio](https://www.owox.com/data-destinations/looker-studio) — /data-destinations/looker-studio.md - [OWOX MCP](https://www.owox.com/features/mcp) — /features/mcp.md - [Book a Demo](https://www.owox.com/book-a-call) — /book-a-call.md - [pricing](https://www.owox.com/pricing) — /pricing.md - [Facebook Ads → Google Sheets guide](https://www.owox.com/blog/articles/free-facebook-ads-connector-to-google-sheets) — /blog/articles/free-facebook-ads-connector-to-google-sheets.md - [unified ad report guide](https://www.owox.com/blog/articles/unified-ad-report-google-sheets) — /blog/articles/unified-ad-report-google-sheets.md - [governed MCP analytics](https://www.owox.com/blog/articles/governed-mcp-analytics) — /blog/articles/governed-mcp-analytics.md - [sign up](https://www.owox.com/app-signup) - [Google BigQuery · Build GA4 BigQuery Dashboard in Looker Studio in 2025 · February 24, 2025](https://www.owox.com/blog/articles/ga4-bigquery-export-building-looker-studio-dashboard) — /blog/articles/ga4-bigquery-export-building-looker-studio-dashboard.md - [Data Integration · Free Facebook Ads to BigQuery connector by OWOX · October 1, 2026](https://www.owox.com/blog/articles/free-facebook-ads-to-bigquery-connector) — /blog/articles/free-facebook-ads-to-bigquery-connector.md - [Data Integration · Free TikTok Ads to BigQuery connector by OWOX · October 1, 2026](https://www.owox.com/blog/articles/free-tiktok-ads-to-bigquery-connector) — /blog/articles/free-tiktok-ads-to-bigquery-connector.md - [See all articles →](https://www.owox.com/blog/articles) — /blog/articles.md