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Databases · head to head

DuckDB vs SurrealDB

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
SurrealDB logo

SurrealDB

Databases

Multi-model database combining documents, graphs, vectors and time-series

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.; SurrealDB the listed $0.192/node/hr Scale pricing lacks transparent higher-tier rates, requiring a sales conversation for full production sizing.
  • They diverge on capability: DuckDB covers In-process execution, SurrealDB covers Multi-model engine.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and SurrealDB actually diverge.

Attributes where DuckDB and SurrealDB differ
AttributeDuckDBSurrealDB
Pricing modelopen-sourceusage-based
PlatformsLinux, macOS, Windows, WebAssemblyweb, api, windows, mac, linux
Founded20192022

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 SurrealDB

  • Multi-model engine
  • ACID transactions
  • Hybrid retrieval
  • Horizontal scaling
  • Multi-region disaster recovery
  • FIPS-compliant cryptography

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

SurrealDB

  • AI agent memory and retrieval-augmented generationnot DuckDB
  • Applications needing documents, graphs and vectors in one databasenot DuckDB
  • Knowledge graph construction from unstructured datanot DuckDB
  • Regulated workloads requiring SOC2/ISO27001/HIPAA-eligible hostingnot 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.

SurrealDB

  • The listed $0.192/node/hr Scale pricing lacks transparent higher-tier rates, requiring a sales conversation for full production sizing.
  • As a newer multi-model database, it has a smaller ecosystem of drivers, ORMs and community tooling than established single-model databases.
  • HIPAA compliance is only available as an Enterprise add-on rather than included in standard paid tiers.
  • Combining multiple data models in one engine can add query-planning complexity compared to purpose-built single-model databases.

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

SurrealDB

Free
  • StartFree
    • 1 free instance, then from $0.021/hr
    • 1GB storage free forever
    • Vertical scaling to terabytes
  • Scale$0.192/month
    • $0.192/node/hr
    • Production-grade fault tolerance
    • Horizontal scaling to petabytes
  • Enterprise$undefined/month
    • Self-hosted, custom pricing
    • Clustered fault-tolerant deployments
    • FIPS-compliant cryptography

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 SurrealDB if

  • You need multi-model engine.
  • You want to start without paying.
  • You work on web, api, windows, mac, linux.
  • You also want acid transactions.
SurrealDB review

Questions people ask

Is DuckDB or SurrealDB better?
Neither clearly leads. DuckDB starts at Free and SurrealDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or SurrealDB?
DuckDB starts at Free and SurrealDB at Free.
Does DuckDB or SurrealDB run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. SurrealDB runs on web, api, windows, mac, 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 SurrealDB is typically brought in for.
What can DuckDB do that SurrealDB cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. SurrealDB covers Multi-model engine, ACID transactions, Hybrid retrieval, Horizontal scaling.

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.

SurrealDB: What does SurrealDB cost?

SurrealDB Cloud's Start plan is free with one free instance (then from $0.021/hr), the Scale plan runs $0.192/node/hr for production workloads, and Enterprise self-hosted deployments use custom pricing.

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.

SurrealDB: Is there a free plan and what are its limits?

Yes, the Start plan includes one free instance with 1GB of storage free forever and 1GB of outbound data transfer per month, aimed at prototypes and development.

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.

SurrealDB: How is billing handled?

Customers are invoiced monthly based on actual usage in a pay-as-you-go model with no long-term commitments, though commitment-based discounts are available.

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.

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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