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Databases · head to head

DuckDB vs Yellowfin

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
Yellowfin logo

Yellowfin

Business Intelligence

Action-based business intelligence

From
$50/month
Rated
-
Full reviewWebsite

The short version

  • Only DuckDB has a free tier, so it costs nothing to try first.
  • 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.; Yellowfin the pricing page publishes no rate, no minimum and no per-user price; every model ends in a Get Pricing form
  • They diverge on capability: DuckDB covers In-process execution, Yellowfin covers Automated Analysis.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and Yellowfin actually diverge.

Attributes where DuckDB and Yellowfin differ
AttributeDuckDBYellowfin
Starting priceFree$50/month
Pricing modelopen-sourcesubscription
Free tierYesNo
PlatformsLinux, macOS, Windows, WebAssemblyWeb, Mobile, Embedded
CategoryDatabasesBusiness Intelligence
Founded20192003

Identical on both: 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 Yellowfin

  • Automated Analysis
  • Data Stories
  • Collaboration
  • Signals
  • Embedded Analytics
  • Salesforce
  • Google Analytics
  • SQL Server

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

Yellowfin

  • Embedding white-labelled dashboards and analytics into a software productnot DuckDB
  • Enterprise reporting with automated business monitoring and alertingnot DuckDB
  • Data storytelling and guided natural language querying for business usersnot 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.

Yellowfin

  • The pricing page publishes no rate, no minimum and no per-user price; every model ends in a Get Pricing form
  • One of the three embedded models is a revenue share, so Yellowfin takes a cut of the revenue your analytics module earns
  • Another model prices by server core, so scaling deployment hardware raises the licence cost independently of users
  • Getting a quote requires submitting a form with a marketing consent checkbox and a user-count band rather than seeing a rate card

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Yellowfin

$50/month
  • Team$50/month
    • Dashboards
    • Stories
    • Collaboration
  • EnterpriseFree
    • Advanced Features
    • Embedding
    • Custom SLA

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 Yellowfin if

  • You need automated analysis.
  • You work on Web, Mobile, Embedded.
  • You also want data stories.
Yellowfin review

Questions people ask

Is DuckDB or Yellowfin better?
Neither clearly leads. DuckDB starts at Free and Yellowfin at $50/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or Yellowfin?
DuckDB has a free tier; the other does not. Paid plans start at Free for DuckDB and $50/month for Yellowfin.
Does DuckDB or Yellowfin run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. Yellowfin runs on Web, Mobile, Embedded.
Can I use DuckDB for free?
Yes. DuckDB has a free tier, so you can try it without paying. Yellowfin starts at $50/month.
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 Yellowfin is typically brought in for.
What can DuckDB do that Yellowfin cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. Yellowfin covers Automated Analysis, Data Stories, Collaboration, Signals.

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.

Yellowfin: What pricing models does Yellowfin offer?

Yellowfin offers three flexible models for embedded analytics: Aligned Utility Model (price per unit), Revenue Share Model (based on analytics revenue value), and Server Core (fixed price based on server deployment).

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.

Yellowfin: Is Yellowfin pricing predictable and scalable?

Yes, Yellowfin pricing is simple, predictable and scalable with no hidden costs or surprises.

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.

Yellowfin: Are there limits on user access or development environments?

No limitations exist on access to functionality across users. There are also no limits on dev and test licenses, ensuring DevOps is covered.

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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