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Databases · head to head

DuckDB vs Turso

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
Turso logo

Turso

Databases

SQLite-lineage database platform for running very large numbers of small per-tenant databases, with an MIT-licensed engine.

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.; Turso sQLite allows one writer per database, so a single tenant's write throughput cannot be scaled horizontally and a busy tenant serialises against itself with no sharding option.
  • They diverge on capability: DuckDB covers In-process execution, Turso covers Per-tenant databases.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and Turso actually diverge.

Attributes where DuckDB and Turso differ
AttributeDuckDBTurso
Pricing modelopen-sourcefreemium
PlatformsLinux, macOS, Windows, WebAssemblyWeb
Founded2019Unknown

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
  • Postgres-flavoured SQL
  • Extension ecosystem
  • Stable storage format

Only in Turso

  • Per-tenant databases
  • Embedded replicas
  • SQLite compatibility
  • HTTP access
  • Branching
  • Point-in-time restore
  • In-process engine
  • Platform API

Both cover

  • MIT licence

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

Turso

  • Multi-tenant SaaS where each customer gets their own database for real isolation, per-tenant restore and clean deletionnot DuckDB
  • Agent or session infrastructure that creates a throwaway database per task and destroys it afterwardsnot DuckDB
  • Local-first and offline-capable applications where an embedded replica serves reads at file speed and syncs when connectivity returnsnot DuckDB
  • Embedding a SQLite-compatible engine in a product where the public domain original's closed contribution model is a problemnot 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.

Turso

  • SQLite allows one writer per database, so a single tenant's write throughput cannot be scaled horizontally and a busy tenant serialises against itself with no sharding option.
  • Per-tenant databases mean per-tenant migrations, so every schema change becomes a fan-out job that must be idempotent and resumable, and multi-database schemas, the feature meant to solve this, is deprecated.
  • There are no cross-database queries; ATTACH is deprecated on the cloud, so any report or analytic spanning tenants must be assembled in your application or in a separate warehouse you also operate.
  • Data Edge, the multi-region edge replication that was Turso's original positioning, is deprecated, so a large share of the tutorials and articles describing Turso as an edge database describe behaviour you can no longer rely on.
  • Three engine lineages share the name, SQLite, the libSQL fork and the Rust rewrite, and the Rust engine is still maturing, so SQLite compatibility needs verifying against your specific pragmas, extensions and query patterns; the cloud already restricts journal_mode and busy_timeout and makes user_version read-only.

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Turso

Free
  • FreeFree
    • 100 databases
    • 5 GB storage
    • 500M monthly rows read
  • Developer$4.99/month
    • Unlimited databases
    • 9 GB storage
    • 2.5B monthly rows read
  • Scaler$24.92/month
    • Unlimited databases
    • 24 GB storage
    • 100B monthly rows read
  • Pro$416.58/month
    • Unlimited databases
    • 50 GB storage
    • 250B monthly rows read

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 Turso if

  • You need per-tenant databases.
  • You want to start without paying.
  • You also want embedded replicas.
Turso review

Questions people ask

Is DuckDB or Turso better?
Neither clearly leads. DuckDB starts at Free and Turso at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or Turso?
DuckDB starts at Free and Turso at Free.
Does DuckDB or Turso run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. Turso runs on Web.
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 Turso is typically brought in for.
What can DuckDB do that Turso cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. Turso covers Per-tenant databases, Embedded replicas, SQLite compatibility, HTTP access. Both handle MIT licence.

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.

Turso: Is Turso just hosted SQLite?

Not exactly. It hosts databases built on the SQLite lineage: libSQL, an MIT fork of SQLite, and Turso Database, a newer Rust rewrite. The platform adds branching, backups, an HTTP API and programmatic database creation.

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.

Turso: Can I really run a million databases?

That is the design goal and the platform API exists to make provisioning and deletion programmatic. The practical constraints are the ones that come with it: migrations fan out, and nothing can query across databases.

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.

Turso: How do embedded replicas handle read-after-write?

Reads come from the local replica and writes go to the primary, so a read immediately after a write can return stale data unless you wait for a sync. Application code has to account for that rather than assume it.

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.

Turso: What licence is it under?

libSQL and Turso Database are both MIT. Turso Cloud is a commercial managed service built on them, so the engine is genuinely open even though the platform is not.

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.

Turso: Is Turso still an edge database?

No. Data Edge, the multi-region edge replication feature, is deprecated. The current positioning is per-tenant and embedded databases, and older material describing edge replication is out of date.

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