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Databases · head to head

DuckDB vs MySQL

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
MySQL logo

MySQL

Web Development

The world's most popular open source 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.; MySQL hot online backup is not in the free Community Server; MySQL Enterprise Backup is a paid Enterprise Edition component
  • They diverge on capability: DuckDB covers In-process execution, MySQL covers ACID compliance.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and MySQL actually diverge.

Attributes where DuckDB and MySQL differ
AttributeDuckDBMySQL
Pricing modelopen-sourcefreemium
PlatformsLinux, macOS, Windows, WebAssemblyWindows, Macos, Linux, Unix
CategoryDatabasesWeb Development
Founded20191995

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 MySQL

  • ACID compliance
  • SQL support
  • Multi-version concurrency control
  • Replication
  • Partitioning
  • Stored procedures
  • Triggers
  • Views

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

MySQL

  • Web application backendnot DuckDB
  • E-commerce platformsnot DuckDB
  • Content management systemsnot DuckDB
  • Data warehousingnot DuckDB
  • Business applicationsnot 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.

MySQL

  • Hot online backup is not in the free Community Server; MySQL Enterprise Backup is a paid Enterprise Edition component
  • Transparent Data Encryption, data masking and de-identification are Enterprise Edition only
  • MySQL Enterprise Firewall, which guards against SQL injection, and MySQL Enterprise Audit are both paid components
  • External authentication against PAM or Windows Active Directory requires MySQL Enterprise Authentication
  • The thread pool ships as MySQL Enterprise Scalability rather than in the community build

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

MySQL

Free
  • Community EditionFree
    • Open source license
    • Full SQL support
    • InnoDB storage engine
  • Standard Edition$2000/year
    • Commercial license
    • Oracle Premier Support
    • MySQL Enterprise backup
  • Enterprise Edition$5000/year
    • Advanced security
    • MySQL Enterprise Monitor
    • High Availability

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 MySQL if

  • You need acid compliance.
  • You want to start without paying.
  • You work on Windows, Macos, Linux, Unix.
  • You also want sql support.
MySQL review

Questions people ask

Is DuckDB or MySQL better?
Neither clearly leads. DuckDB starts at Free and MySQL at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or MySQL?
DuckDB starts at Free and MySQL at Free.
Does DuckDB or MySQL run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. MySQL runs on Windows, Macos, Linux, 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 MySQL is typically brought in for.
What can DuckDB do that MySQL cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. MySQL covers ACID compliance, SQL support, Multi-version concurrency control, Replication.

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.

MySQL: Does MySQL cost money?

MySQL is primarily open-source and free to use. Commercial editions and support services are available but pricing is not published on the main website.

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.

MySQL: How do I get MySQL pricing information?

For MySQL commercial editions and support pricing, customers can contact MySQL sales directly at +1-866-221-0634 or navigate to individual product pages.

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.

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