Softwr

Databases · head to head

DuckDB vs PocketBase

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
PocketBase logo

PocketBase

APIs

Open-source backend with REST API, real-time subscriptions and Admin UI

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.; PocketBase requires technical expertise to deploy and maintain
  • They diverge on capability: DuckDB covers In-process execution, PocketBase covers REST API.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and PocketBase actually diverge.

Attributes where DuckDB and PocketBase differ
AttributeDuckDBPocketBase
Pricing modelopen-sourceUnknown
PlatformsLinux, macOS, Windows, WebAssemblyLinux, Windows, macOS, FreeBSD
CategoryDatabasesAPIs
Founded20192021

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 PocketBase

  • REST API
  • Real-time subscriptions
  • Admin UI
  • SQLite
  • Webhooks
  • File storage
  • Go support
  • Docker support

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 PocketBase
  • Analytical queries embedded in an application or a dashboard where shipping a database server alongside it is not acceptablenot PocketBase
  • Local exploration of files that are too large for a pandas dataframe but far too small to justify a warehousenot PocketBase
  • Continuous integration and testing of analytical SQL, where a real engine can run in the test process without provisioning anythingnot PocketBase

PocketBase

  • Embedded realtime database with REST APInot DuckDB
  • Backend-as-a-service for single-file deploymentsnot DuckDB
  • Rapid application development with email/OAuth2 authenticationnot DuckDB
  • File storage and media attachment managementnot DuckDB
  • Lightweight alternative to Firebase or traditional backend infrastructurenot DuckDB
  • Go and JavaScript customisable application frameworknot 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.

PocketBase

  • Requires technical expertise to deploy and maintain
  • No built-in hosting provided
  • Community support only

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

PocketBase

Free

No published plan breakdown. See the PocketBase review.

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 PocketBase if

  • You need rest api.
  • You want to start without paying.
  • You work on Linux, Windows, macOS, FreeBSD.
  • You also want real-time subscriptions.
PocketBase review

Questions people ask

Is DuckDB or PocketBase better?
Neither clearly leads. DuckDB starts at Free and PocketBase at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or PocketBase?
DuckDB starts at Free and PocketBase at Free.
Does DuckDB or PocketBase run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. PocketBase runs on Linux, Windows, macOS, FreeBSD.
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 PocketBase is typically brought in for.
What can DuckDB do that PocketBase cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. PocketBase covers REST API, Real-time subscriptions, Admin UI, SQLite.

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.

PocketBase: How much does PocketBase cost?

PocketBase is completely free and open-source. It is a self-hosted backend solution with database, authentication, and file storage capabilities at no cost.

Source
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.

PocketBase: Is PocketBase open-source?

Yes, PocketBase is open-source software. You can download, modify, and deploy it yourself at no cost with no licensing restrictions.

Source
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.

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.

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.

Share

Related pages

More on DuckDB

More on PocketBase

Keep looking

Other head to heads