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Databases · head to head

DuckDB vs PostgreSQL

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
PostgreSQL logo

PostgreSQL

Databases

The world's most advanced open source relational database

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.; PostgreSQL requires manual scaling across multiple machines for very large deployments
  • They diverge on capability: DuckDB covers In-process execution, PostgreSQL covers ACID Compliance.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and PostgreSQL actually diverge.

Attributes where DuckDB and PostgreSQL differ
AttributeDuckDBPostgreSQL
Pricing modelopen-sourceUnknown
PlatformsLinux, macOS, Windows, WebAssemblyLinux, Windows, macOS, BSD, Unix
Founded20191996

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

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 PostgreSQL

  • ACID Compliance
  • JSON/JSONB Support
  • Full-text Search
  • Extensibility
  • Advanced Indexing
  • Partitioning
  • Replication
  • pgAdmin

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

PostgreSQL

  • Transaction processingnot DuckDB
  • Data storagenot DuckDB
  • Application backendnot DuckDB
  • Reportingnot DuckDB
  • Data analyticsnot 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.

PostgreSQL

  • Requires manual scaling across multiple machines for very large deployments
  • Performance tuning requires deep knowledge of database internals
  • No built-in graphical admin interface; command-line tools are primary method

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

PostgreSQL

Free

No published plan breakdown. See the PostgreSQL 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 PostgreSQL if

  • You need acid compliance.
  • You want to start without paying.
  • You work on Linux, Windows, macOS, BSD, Unix.
  • You also want json/jsonb support.
PostgreSQL review

Questions people ask

Is DuckDB or PostgreSQL better?
Neither clearly leads. DuckDB starts at Free and PostgreSQL at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or PostgreSQL?
DuckDB starts at Free and PostgreSQL at Free.
Does DuckDB or PostgreSQL run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. PostgreSQL runs on Linux, Windows, macOS, BSD, Unix.
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 PostgreSQL is typically brought in for.
What can DuckDB do that PostgreSQL cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. PostgreSQL covers ACID Compliance, JSON/JSONB Support, Full-text Search, Extensibility.

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.

PostgreSQL: Is PostgreSQL completely free?

Yes. PostgreSQL is completely free and open source with no licensing fees or restrictions on use.

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.

PostgreSQL: What platforms does PostgreSQL run on?

PostgreSQL runs on all major operating systems including Linux, Windows, macOS, BSD, and commercial Unix variants, and has been proven highly scalable managing terabytes to petabytes of data.

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.

PostgreSQL: What procedural languages are supported?

PostgreSQL supports stored functions and procedures in multiple languages including PL/pgSQL, Perl, Python, Tcl, Java, JavaScript, R, and Rust.

Source
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.

PostgreSQL: What is ACID compliance in PostgreSQL?

PostgreSQL has been ACID-compliant since 2001, ensuring data integrity through atomicity, consistency, isolation, and durability guarantees for all transactions.

Source
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.

PostgreSQL: Does PostgreSQL support JSON data?

Yes. PostgreSQL supports JSON and JSONB data types for storing and querying JSON documents, along with XML and other document formats.

Source
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