Databricks Buys Row Zero to Add Live, Governed Spreadsheets
Databricks announced on September 24, 2026 that it has acquired Row Zero. Terms of the deal were not disclosed TechCrunch.
Row Zero was founded by former AWS and Tableau engineers. It raised $10 million in May 2025 at an estimated $40 million valuation TechCrunch. Its product is a cloud spreadsheet designed to work with more than one million live rows.
Standard spreadsheets slow down or fail well below that size. Analysts then have to use samples, export files, or split data into separate static sheets. Row Zero keeps the familiar grid of rows and columns, but it connects to live datasets that would normally need SQL, the language for querying databases, Python, a general programming language, or a BI semantic layer, a defined set of business terms that sits between raw data and charts.
Databricks said in its official newsroom release that "Row Zero will combine the simplicity and flexibility of spreadsheets with built-in auditability, security, and governance" Databricks. Row Zero confirmed the deal separately on its own website.
Databricks closed $5 billion in funding in August 2026 and reported a $7 billion annualized revenue run rate as of September 2026 TechCrunch. CEO Ali Ghodsi said the company plans many more acquisitions like Row Zero in the future.
Row Zero follows several recent buys. In March 2026, Databricks acquired Quotient AI, which works on evaluation and reinforcement learning for AI agents, and SiftD.ai, a very early-stage interactive notebook startup. In June 2026, it acquired Panther, an AI security operations center startup previously valued at $1.4 billion in 2021. In August 2026, it acquired Electric, the maker of PGlite, a lightweight version of the Postgres database TechCrunch.
Databricks maintains formal channels for finding such targets. Databricks Ventures invests in innovative companies that share Databricks' view of the future for data, analytics and AI. The 2026 Built-On Databricks Startup Challenge was a global competition for early-stage B2B startups building core products on Databricks.
The broader context here is that spreadsheets are still where most business modeling happens. They are fast, flexible, and controlled by the end user. They also sit outside permissioning, lineage, the record of where data came from, and audit controls. Vendors have tried to fix this by moving users into governed BI tools or by copying warehouse tables into static sheets. The first option removes flexibility and the second breaks the link to the source once data is exported, so neither has held.
In my view, the bet is that governance can be built into the spreadsheet itself rather than added around it. The practical questions are how live the connection is, which query engine runs the grid calculations, how edits in cells map back to governed tables, and how access controls, audit logs, and data masking hold up when a finance user shares a workbook outside the company. If Databricks can handle those without forcing users to rewrite existing spreadsheet logic, it will have a direct interface for business users who will never open a notebook. That would extend its reach from data engineering and AI work into operational analytics, where spreadsheets still guide decisions. It is also worth flagging that early spreadsheet engines often have trouble with many users editing at once, consistent calculations, and AI-generated formulas at scale. Solving those problems inside a governed platform is harder than building a fast grid, and it will decide whether this becomes everyday infrastructure.
