Spreadsheets · head to head
APITable vs DuckDB
APITable
Spreadsheets
Open source spreadsheet database with an API first design and an embeddable widget system
- From
- Free
- Rated
- -
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: APITable records are held in the product own schema rather than as native database tables, so the practical row ceiling is a product limit and large tables should be load tested before commitment.; 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: APITable covers API first design, DuckDB covers In-process execution.
- Prices and features above were last checked on 31 August 2026.
Where they differ
Only the attributes on which APITable and DuckDB actually diverge.
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 APITable
- API first design
- Widget SDK
- Embeddable views
- Multiple view types
- Linked records and formulas
- Self hosting
- Real time collaboration
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.
APITable
- Embedding an editable table view inside a product you are building, rather than sending users to another toolnot DuckDB
- An internal platform where tables are read and written mostly by code through the API and only occasionally by peoplenot DuckDB
- A self hosted replacement for a per seat spreadsheet database where seat count is the cost drivernot DuckDB
- Building a custom dashboard widget that sits beside the data instead of in a separate reporting toolnot DuckDB
DuckDB
- Transformation steps in a data pipeline that would otherwise need Spark, replaced by SQL over Parquet in a single processnot APITable
- Analytical queries embedded in an application or a dashboard where shipping a database server alongside it is not acceptablenot APITable
- Local exploration of files that are too large for a pandas dataframe but far too small to justify a warehousenot APITable
- Continuous integration and testing of analytical SQL, where a real engine can run in the test process without provisioning anythingnot APITable
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
APITable
- Records are held in the product own schema rather than as native database tables, so the practical row ceiling is a product limit and large tables should be load tested before commitment.
- The hosted free tier caps records per space, so evaluating on the cloud version gives a misleading picture of what the software can do when self hosted.
- Automation is thin compared with the commercial alternatives, and most real workflows end up in an external automation tool.
- The self hosted deployment is heavier than a single container, so running it properly means managing several services rather than one.
- Documentation and community activity are uneven in English, and finding an answer to an operational problem can take longer than the problem itself deserves.
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
APITable
Free- Self hosted open sourceFree
- No licence fee
- No product record cap on self hosted deployments
- Docker and Kubernetes deployment
DuckDB
FreeNo published plan breakdown. See the DuckDB review.
Which should you pick?
Choose APITable if
- You need api first design.
- You want to start without paying.
- You work on Web, Linux.
- You also want widget sdk.
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 APITable or DuckDB better?
- Neither clearly leads. APITable 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, APITable or DuckDB?
- APITable starts at Free and DuckDB at Free.
- Does APITable or DuckDB run on more platforms?
- APITable runs on Web, Linux. DuckDB runs on Linux, macOS, Windows, WebAssembly.
- Can I use APITable for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is APITable best used for?
- APITable is most often used for embedding an editable table view inside a product you are building, rather than sending users to another tool, an internal platform where tables are read and written mostly by code through the api and only occasionally by people, a self hosted replacement for a per seat spreadsheet database where seat count is the cost driver, building a custom dashboard widget that sits beside the data instead of in a separate reporting tool. Of those, embedding an editable table view inside a product you are building, rather than sending users to another tool and an internal platform where tables are read and written mostly by code through the api and only occasionally by people are not what DuckDB is typically brought in for.
- What can APITable do that DuckDB cannot?
- APITable covers API first design, Widget SDK, Embeddable views, Multiple view types. DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies.
Answered from the vendors’ own pages
APITable: What is the record limit?
The self hosted edition has no product cap, but performance is bounded by the internal schema rather than by your database. Test at your expected size.
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.
APITable: Can I embed it in my own product?
Yes, and that is the main reason to choose it. Views embed and the widget SDK extends them.
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.
APITable: Is the hosted version representative?
No. Its free tier caps records per space, which is a commercial limit rather than a technical one.
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.
APITable: How hard is self hosting?
Harder than a single container. Plan for several services and someone to keep them running.
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.
APITable: Does it do automations?
Lightly. Expect to pair it with an external automation tool for anything multi step.
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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