Spreadsheets · head to head
Baserow vs DuckDB
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
- -
The short version
- Each has a real cost: Baserow the free tier is capped at 3,000 rows and 2GB of storage per workspace; 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.
- They diverge on capability: Baserow covers Database tables, DuckDB covers In-process execution.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Baserow and DuckDB actually diverge.
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), founded (2019).
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 Baserow
- Database tables
- Multiple views
- Forms
- API access
- Real-time collaboration
- Templates
- Plugins
- Self-hosting
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
What people use each for
The jobs each tool is most often brought in to do.
Baserow
- Self-hosting an open source alternative to a spreadsheet databasenot DuckDB
- Structured team data with Kanban, calendar and grid viewsnot DuckDB
- Building internal tools on top of a database with an APInot DuckDB
- Sharing data with external app users without giving them full seatsnot DuckDB
DuckDB
- Transformation steps in a data pipeline that would otherwise need Spark, replaced by SQL over Parquet in a single processnot Baserow
- Analytical queries embedded in an application or a dashboard where shipping a database server alongside it is not acceptablenot Baserow
- Local exploration of files that are too large for a pandas dataframe but far too small to justify a warehousenot Baserow
- Continuous integration and testing of analytical SQL, where a real engine can run in the test process without provisioning anythingnot Baserow
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Baserow
- The free tier is capped at 3,000 rows and 2GB of storage per workspace
- Kanban, calendar and survey views need Premium at $10 per user per month billed yearly
- Role-based permissions, audit logs and SSO require Premium or higher
- Row limits are per workspace rather than per table, so splitting data across bases does not raise the ceiling
- Automation runs are metered as credits, 2,000 a month on free
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.
Pricing, plan by plan
Baserow
Free- FreeFree
- 3000 rows per workspace
- 2 GB storage per workspace
- 2000 automation credits monthly
- Premium$10/month
- 50000 rows per workspace
- 20 GB storage per workspace
- 100000 automation credits monthly
- Advanced$18/month
- 250000 rows per workspace
- 100 GB storage per workspace
- 500000 automation credits monthly
- Enterprise$null/month
- 1000000 rows per workspace
- 1000 GB storage per workspace
- 2000000 automation credits monthly
DuckDB
FreeNo published plan breakdown. See the DuckDB review.
Which should you pick?
Choose Baserow if
- You need database tables.
- You want to start without paying.
- You work on Web, Api, Self-hosted.
- You also want multiple views.
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.
Questions people ask
- Is Baserow or DuckDB better?
- Neither clearly leads. Baserow starts at Free and DuckDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Baserow or DuckDB?
- Baserow starts at Free and DuckDB at Free.
- Does Baserow or DuckDB run on more platforms?
- Baserow runs on Web, Api, Self-hosted. DuckDB runs on Linux, macOS, Windows, WebAssembly.
- Can I use Baserow for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Baserow best used for?
- Baserow is most often used for self-hosting an open source alternative to a spreadsheet database, structured team data with kanban, calendar and grid views, building internal tools on top of a database with an api, sharing data with external app users without giving them full seats. Of those, self-hosting an open source alternative to a spreadsheet database and structured team data with kanban, calendar and grid views are not what DuckDB is typically brought in for.
- What can Baserow do that DuckDB cannot?
- Baserow covers Database tables, Multiple views, Forms, API access. DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies.
Answered from the vendors’ own pages
Baserow: Does Baserow have a free plan?
Baserow's Free plan includes 3000 rows per workspace, 2 GB storage, 2000 automation credits monthly, and access to Grid, Form, and Gallery views. It supports up to 500 external app users and includes 65+ templates with no credit card required.
SourceDuckDB: 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.
Baserow: What row and storage limits does Baserow provide by plan?
Free plan: 3000 rows and 2 GB storage; Premium plan: 50000 rows and 20 GB; Advanced plan: 250000 rows and 100 GB; Enterprise plan: 1000000 rows and 1 TB. All limits are per workspace.
SourceDuckDB: 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.
Baserow: How much does Baserow Premium cost?
Baserow Premium costs $10 per user per month when billed annually, or $12 per month when billing monthly. Yearly billing provides better rates than monthly. Advanced plan costs $18/user/month annually or $22/month monthly.
SourceDuckDB: 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.
Baserow: What are automation credit limits in Baserow?
Free plan provides 2000 monthly automation credits, Premium provides 100000 monthly credits, Advanced provides 500000 monthly credits, and Enterprise provides 2000000 monthly credits for workflow automation.
SourceDuckDB: 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.
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.
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