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Databases · head to head

DuckDB vs Vitess

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
Vitess logo

Vitess

Databases

Scalable database clustering system for horizontal scaling of MySQL

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.; Vitess vTGate scatter queries without sharding key incur significant performance penalties
  • They diverge on capability: DuckDB covers In-process execution, Vitess covers Horizontal Sharding.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and Vitess actually diverge.

Attributes where DuckDB and Vitess differ
AttributeDuckDBVitess
Pricing modelopen-sourceUnknown
PlatformsLinux, macOS, Windows, WebAssemblyLinux, macOS, Docker, Kubernetes
Founded20192010

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 Vitess

  • Horizontal Sharding
  • Connection Pooling
  • Query Routing
  • Online Schema Changes
  • Shard Management
  • Replication Management
  • Automated Failover
  • MySQL

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

Vitess

  • 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.

Vitess

  • VTGate scatter queries without sharding key incur significant performance penalties
  • Foreign key constraints not enforced across shards, requiring application-level integrity handling
  • Single primary per keyspace limits multi-region write capabilities
  • Distributed transactions without proper sharding key routing suffer performance degradation

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Vitess

Free

No published plan breakdown. See the Vitess 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 Vitess if

  • You need horizontal sharding.
  • You want to start without paying.
  • You work on Linux, macOS, Docker, Kubernetes.
  • You also want connection pooling.
Vitess review

Questions people ask

Is DuckDB or Vitess better?
Neither clearly leads. DuckDB starts at Free and Vitess at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or Vitess?
DuckDB starts at Free and Vitess at Free.
Does DuckDB or Vitess run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. Vitess runs on Linux, macOS, Docker, Kubernetes.
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 Vitess is typically brought in for.
What can DuckDB do that Vitess cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. Vitess covers Horizontal Sharding, Connection Pooling, Query Routing, Online Schema Changes.

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.

Vitess: Is Vitess free to use?

Yes. Vitess is completely free and open source under the Apache 2.0 license. It is a graduated CNCF project with no licensing costs or pricing tiers.

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.

Vitess: What databases does Vitess support?

Vitess supports MySQL and MariaDB as backend databases. It acts as a middleware layer that adds sharding and orchestration capabilities on top of these databases.

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.

Vitess: Does Vitess require Kubernetes to run?

No. Vitess can run on Kubernetes using the Vitess Operator, but it can also be deployed on traditional infrastructure. Kubernetes integration is optional and provides additional automation benefits.

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.

Vitess: How does Vitess handle cross-shard transactions?

Vitess supports distributed transactions across shards, but they require queries to be routed through the sharding key. Transactions without a proper sharding key can result in slower performance.

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.

Vitess: Does Vitess enforce foreign key constraints?

Vitess does not enforce foreign key constraints across shards by default. Referential integrity must be managed at the application layer, though per-database support can be enabled with limitations.

Source
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