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Databases · head to head

DuckDB vs Mathesar

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
Mathesar logo

Mathesar

Spreadsheets

Spreadsheet style interface that edits an existing PostgreSQL database directly, with no schema of its own

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.; Mathesar there is no hosted offering of any kind, so a team without someone who can run and secure a server cannot use it at all.
  • They diverge on capability: DuckDB covers In-process execution, Mathesar covers Direct PostgreSQL editing.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which DuckDB and Mathesar actually diverge.

Attributes where DuckDB and Mathesar differ
AttributeDuckDBMathesar
Pricing modelopen-sourceOpen source, no licence fee
PlatformsLinux, macOS, Windows, WebAssemblyWeb, Linux
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 Mathesar

  • Direct PostgreSQL editing
  • PostgreSQL permissions
  • Schema editing
  • Data exploration
  • Relationship navigation
  • Import of tabular files
  • Self hosted only

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

Mathesar

  • A nonprofit or research group whose data is already in PostgreSQL and whose staff cannot write SQLnot DuckDB
  • Giving analysts a safe editing interface governed by database roles that already existnot DuckDB
  • Replacing a hand built Django or Rails admin screen that nobody wants to maintainnot DuckDB
  • Editing production reference data where an export, edit and reimport cycle would risk losing concurrent changesnot 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.

Mathesar

  • There is no hosted offering of any kind, so a team without someone who can run and secure a server cannot use it at all.
  • It works only with PostgreSQL, so a MySQL, SQL Server or SQLite estate is excluded outright.
  • There are no automations, no webhooks and effectively no integration catalogue, so it edits data and does nothing else.
  • Because it writes to the live database, a careless bulk edit or column type change is a production change with no staging step and no undo.
  • Development is grant and community funded rather than commercially funded, so roadmap pace and long term continuity carry a different risk profile from a venture backed vendor.

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Mathesar

Free
  • Self hosted open sourceFree
    • No licence fee
    • No hosted option offered
    • Connects to your existing PostgreSQL database

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 Mathesar if

  • You need direct postgresql editing.
  • You want to start without paying.
  • You work on Web, Linux.
  • You also want postgresql permissions.
Mathesar review

Questions people ask

Is DuckDB or Mathesar better?
Neither clearly leads. DuckDB starts at Free and Mathesar at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or Mathesar?
DuckDB starts at Free and Mathesar at Free.
Does DuckDB or Mathesar run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. Mathesar runs on Web, Linux.
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 Mathesar is typically brought in for.
What can DuckDB do that Mathesar cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. Mathesar covers Direct PostgreSQL editing, PostgreSQL permissions, Schema editing, Data exploration.

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.

Mathesar: Is there a cloud version?

No. Self hosting is the only option, and that is a deliberate project decision rather than a gap waiting to be filled.

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.

Mathesar: How does it handle permissions?

Through PostgreSQL roles and privileges directly, so there is no second permission model to keep in step.

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.

Mathesar: What is the row limit?

Whatever PostgreSQL can handle. Mathesar adds no storage layer of its own.

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.

Mathesar: Does it support databases other than PostgreSQL?

No.

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.

Mathesar: Can it replace Airtable?

Only for editing and exploring data. There are no automations, apps or integrations.

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