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Databases · head to head

DuckDB vs Rowy

DuckDB logo

DuckDB

Databases

MIT-licensed analytical SQL database that runs inside your process, with no server, no dependencies and one writer at a time.

From
Free
Rated
-
Full reviewWebsite
Rowy logo

Rowy

Spreadsheets

Spreadsheet interface for Google Cloud Firestore with cloud functions written in the browser

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: DuckDB a database file accepts one read-write process at a time; other processes must open it read-only and will not see subsequent writes, so DuckDB cannot be the shared database behind several services.; Rowy every Firestore limit is inherited, including the one megabyte per document ceiling and roughly one sustained write per second per document, which surprises users who expect spreadsheet behaviour.
  • They diverge on capability: DuckDB covers In-process execution, Rowy covers Firestore backed grid.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which DuckDB and Rowy actually diverge.

Attributes where DuckDB and Rowy differ
AttributeDuckDBRowy
Pricing modelopen-sourceOpen source, no licence fee
PlatformsLinux, macOS, Windows, WebAssemblyWeb
CategoryDatabasesSpreadsheets
Founded2019Unknown

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in DuckDB

  • In-process execution
  • Vectorised columnar engine
  • Direct file querying
  • Zero dependencies
  • Larger-than-memory queries
  • MIT licence
  • Postgres-flavoured SQL
  • Extension ecosystem

Only in Rowy

  • Firestore backed grid
  • Browser authored cloud functions
  • Typed columns
  • Runs in your Google Cloud project
  • Role based access
  • Form view
  • Open source

What people use each for

The jobs each tool is most often brought in to do.

DuckDB

  • Transformation steps in a data pipeline that would otherwise need Spark, replaced by SQL over Parquet in a single processnot Rowy
  • Analytical queries embedded in an application or a dashboard where shipping a database server alongside it is not acceptablenot Rowy
  • Local exploration of files that are too large for a pandas dataframe but far too small to justify a warehousenot Rowy
  • Continuous integration and testing of analytical SQL, where a real engine can run in the test process without provisioning anythingnot Rowy

Rowy

  • A Firebase application that needs an internal admin interface without building onenot DuckDB
  • Operations staff correcting production records in Firestore without developer involvementnot DuckDB
  • Attaching a small transformation or notification function to a field change without a full deployment pipelinenot DuckDB
  • A content team populating documents that a mobile application reads directly from Firestorenot DuckDB

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

DuckDB

  • A database file accepts one read-write process at a time; other processes must open it read-only and will not see subsequent writes, so DuckDB cannot be the shared database behind several services.
  • There is no network protocol, authentication or user management, so exposing it to remote clients means writing and securing your own service around it.
  • It is built for scans and aggregations, not for many small transactions, so a workload of high-frequency single-row inserts and updates performs badly compared with SQLite or Postgres.
  • Storage files are backwards compatible but not forwards compatible, so a file written by a newer version cannot be read by an older one and every consumer of a shared file must be upgraded together.
  • Query memory settings matter: some operations still need to hold significant state, so an under-configured memory limit turns a large join or a high-cardinality aggregation into a spill-heavy query or an out-of-memory failure rather than a slow success.

Rowy

  • Every Firestore limit is inherited, including the one megabyte per document ceiling and roughly one sustained write per second per document, which surprises users who expect spreadsheet behaviour.
  • Firestore has no joins, so linking tables in the grid is a convenience layer rather than a relational feature and reports across collections still need a separate query.
  • It is useful only to teams already on Firebase, so choosing it effectively locks the operational tooling to one cloud vendor.
  • Query costs are billed by document read, and an unfiltered grid on a large collection can generate a bill that a spreadsheet user has no intuition for.
  • Development activity has slowed relative to the broader category, so evaluate current maintenance before making it load bearing for internal operations.

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Rowy

Free
  • Open source self hostedFree
    • No licence fee
    • Deploys into your own Google Cloud project
    • You pay Google Cloud for Firestore reads, writes and storage

Which should you pick?

Choose DuckDB if

  • You need in-process execution.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, WebAssembly.
  • You also want vectorised columnar engine.
DuckDB review

Choose Rowy if

  • You need firestore backed grid.
  • You want to start without paying.
  • You also want browser authored cloud functions.
Rowy review

Questions people ask

Is DuckDB or Rowy better?
Neither clearly leads. DuckDB starts at Free and Rowy at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or Rowy?
DuckDB starts at Free and Rowy at Free.
Does DuckDB or Rowy run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. Rowy runs on Web.
Can I use DuckDB for free?
Both have a free tier, so you can try either at no cost before committing.
What is DuckDB best used for?
DuckDB is most often used for transformation steps in a data pipeline that would otherwise need spark, replaced by sql over parquet in a single process, analytical queries embedded in an application or a dashboard where shipping a database server alongside it is not acceptable, local exploration of files that are too large for a pandas dataframe but far too small to justify a warehouse, continuous integration and testing of analytical sql, where a real engine can run in the test process without provisioning anything. Of those, transformation steps in a data pipeline that would otherwise need spark, replaced by sql over parquet in a single process and analytical queries embedded in an application or a dashboard where shipping a database server alongside it is not acceptable are not what Rowy is typically brought in for.
What can DuckDB do that Rowy cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. Rowy covers Firestore backed grid, Browser authored cloud functions, Typed columns, Runs in your Google Cloud project.

Answered from the vendors’ own pages

DuckDB: Can multiple applications share one DuckDB database?

Not for writing. One process holds the database read-write; others may attach read-only and will not see later writes. Shared multi-writer access needs a different database or a table format with a catalogue.

Rowy: Where is my data stored?

In your own Firestore instance inside your own Google Cloud project. Rowy does not hold a copy.

DuckDB: Is it a replacement for a data warehouse?

For single-node analytical workloads up to a few hundred gigabytes it very often is. It is not a replacement when many concurrent users need a shared, governed, always-on service.

Rowy: What does it cost to run?

No licence fee. You pay Google Cloud for Firestore reads, writes, storage and function invocations, and an open grid on a big collection reads a lot.

DuckDB: Do I have to load data into it?

No. It queries Parquet, CSV, JSON and Arrow in place, including on object storage. Its own storage format is optional and mainly useful when you want indexes, constraints and faster repeated access.

Rowy: Can it do joins across collections?

Not really. Firestore does not support joins, and no interface layer can add them.

DuckDB: What is MotherDuck's relationship to it?

MotherDuck is a separate company offering a managed and hybrid service built on the DuckDB engine. DuckDB itself remains MIT-licensed and independent of it, with the IP held by the DuckDB Foundation.

Rowy: Is there a row limit?

Not from Rowy. The limits that bite are Firestore document size and per document write throughput.

DuckDB: Is it suitable for OLTP?

No. It is designed for analytical scans. For transactional workloads with frequent small writes, SQLite or Postgres is the right tool.

Rowy: Is it suitable if I am not on Firebase?

No. It is specifically a Firestore interface.

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