Row Zero

What Row Zero is

Row Zero is a cloud spreadsheet built for warehouse-sized data. The company's site calls it "the spreadsheet for modern cloud data," "The spreadsheet for agents and humans," and "a modern data stack for Excel and Google Sheets users." The reader it is written for is an analyst, finance person or operations lead who already works in spreadsheets and needs them to handle huge tables, live connections and governed access. The homepage says Row Zero "brings the security, scale, and live connectivity that enterprise data requires to a spreadsheet your team already knows how to use."

The homepage carries a banner saying Row Zero has been acquired by Databricks, and states it is trusted by over 15,000 companies.

What you build and how

The editor is a familiar grid. The company says you can "Write Excel-compatible formulas, build pivot tables and charts, and create complex spreadsheet models," and that its functions and formulas are compatible with Excel and Google Sheets. You can upload XLSX files directly, so existing workbooks carry over.

Scale is the headline. The homepage lists a maximum spreadsheet size of 2 billion+ rows, describes the product as a cloud spreadsheet "that scales to billion row data sizes," and says it stays fast when you analyze big data. It can open and edit multi-GB CSV files and other formats, with Parquet, JSONL and .gz named on the site. A blog post adds that Row Zero lets you work with database tables in a spreadsheet and code spreadsheet functions to perform complex computations.

The data layer is a set of connections. The homepage lists integrations with Databricks, Snowflake, BigQuery, Oracle, Postgres, Redshift and S3, and the footer adds Athena, SQLServer and Teradata. It describes built-in data connectors with 2-way connections to Snowflake, Databricks, Redshift and more. The idea is a "connected spreadsheet": it auto-updates with the latest data, you can query with SQL, import pre-built data sources, and write back to the data warehouse directly from the sheet. Pivot tables update automatically with new data. Recent product updates on the homepage give a sense of the work under way. One covers a "Standard mode for connected tables" that spills query results into sheet cells, another adds filters on any column when you import a data source, another adds a query builder for BigQuery connections, and another adds sorting in compact or tabular pivot tables.

Code is optional but present. The blog describes a native Python editor: open a workbook, click the Code button, write your code, and click Run; a successful run reports "Build completed." You can then use your custom function in a formula like any built-in one, though the post notes custom formulas do not autocomplete. That gives an analyst a way to write a calculation once in Python and reuse it across a sheet.

For dashboards, the site lists "Dashboards and reports" as a use case. The wording: build recurring reports as connected spreadsheets that auto-update, with "Pivot tables, charts, and slicers" that let you dynamically explore data in real time. The homepage's datasets section shows an example financial spreadsheet and dashboard of 5M rows, with actuals vs forecast, a dashboard sheet and slicers. It also offers a U.S. flights dataset of 26M rows covering 2022 to 2025 with a sample analysis, which works as a template for trying the product on real volume.

The other use cases follow the same pattern. Self-serve analytics gives teams secure access to data warehouse data through one-click data sources. Data wrangling and shaping transforms large raw datasets into clean structured formats. ETL pipelines operationalize and automate big spreadsheet workflows with 2-way connectivity to multiple data sources. Modeling and forecasting builds multi-sheet models on massive datasets connected to live data, using Python for modeling and sensitivity analysis. The site also lists team pages for business intelligence, engineering, finance, healthcare, marketing, operations and logistics.

AI arrives as a spreadsheet assistant. The site describes AI chat in your spreadsheet for analyzing large datasets, "Fully auditable and editable," that takes open-ended prompts and commands, and the feature menu calls it an "AI spreadsheet agent." A resources section lists AI prompts.

Collaboration is multi-user editing and sharing with real-time data updates. Governance is a headline feature: the company says you can "Enable SSO, SCIM, Private Link, and OAuth data connections," and "Enforce row-level security and restrict data export so data never leaves the cloud." The pitch is to replace CSV exports from the warehouse, which the site describes as a security problem, with governed access inside the spreadsheet.

Plans, security and customers

The site publishes no prices on its homepage; the routes in are "Try for free" and "Schedule demo," and the blog invites readers to sign up for free and open a workbook. There is also a Row Zero for Students program and a scholarship listed in the footer.

On security, the site's Security and governance menu lists GDPR, HIPAA, SOC2 and ZDR next to an enterprise security features page and a risk calculator, and the homepage describes SSO, SCIM, Private Link, OAuth connections, row-level security and export controls.

The homepage quotes named users. Peter Cray, VP Strategy and Operations for AWS Sales, Marketing and Global Services, says Row Zero lets "anyone with spreadsheet skills" work "with massive datasets in Amazon Redshift and Amazon S3 at incredible speed and security." Ivan Galea, CTO of Databook, calls it "Incredibly easy for business users to self-serve insights from the data warehouse in a spreadsheet." Rob Harlow, COO of Sopro, says it lets his team "quickly analyze huge datasets using simple and familiar spreadsheet functions." Gentry Davies, CEO of Crew, cites "phenomenal performance, great connectivity, and a price point that was a no brainer." Wes McKinney, creator of Pandas and Apache Arrow, calls it "an impressive feat of engineering, making big data feel small in a familiar spreadsheet interface." Mike Lin, a Sr. Product Development Engineer at Tasso, calls it "the fastest way for our team to analyze and collaborate on giant telemetry datasets." Support comes through documentation, webinars, a community and product update notes.

Who it suits and who it does not

Row Zero suits analysts and finance and operations people whose data lives in a warehouse and whose habits live in a spreadsheet. A team that exports giant CSVs and watches its desktop spreadsheet stall can load the data directly or connect to the warehouse and keep working with formulas and pivot tables. Teams that want some Python without leaving the grid get a native editor, and a data team that wants business users to self-serve without handing out raw exports gets row-level security and export controls.

The caveat is that this is a spreadsheet, not a dashboard design studio. Dashboards here are pivot tables, charts and slicers on a sheet, so a team that wants pixel-level layout or a semantic modeling layer works against the grain. The governance features also point to an organization as the main buyer rather than a hobbyist.