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Databases · head to head

DuckDB vs Fivetran HVR

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
Fivetran HVR logo

Fivetran HVR

Databases

Log-based change data capture for database replication and synchronization

From
On request
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.; Fivetran HVR pricing not published separately; part of Fivetran's usage model
  • They diverge on capability: DuckDB covers In-process execution, Fivetran HVR covers Log-based change capture.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and Fivetran HVR actually diverge.

Attributes where DuckDB and Fivetran HVR differ
AttributeDuckDBFivetran HVR
Starting priceFreeOn request
Pricing modelopen-sourceUsage-based, integrated with Fivetran billing
Free tierYesNo
PlatformsLinux, macOS, Windows, WebAssemblyData Warehouse, Data Lake, Operational Databases
Founded20192012

Identical on both: 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 Fivetran HVR

  • Log-based change capture
  • Real-time replication
  • Schema evolution handling
  • Multi-table consistency
  • Zero-impact monitoring
  • Fivetran integration

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

Fivetran HVR

  • Real-time database replication to data warehousesnot DuckDB
  • Maintaining operational copies for analyticsnot DuckDB
  • Disaster recovery and business continuitynot DuckDB
  • Feeding AI systems with fresh governed datanot 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.

Fivetran HVR

  • Pricing not published separately; part of Fivetran's usage model
  • Requires Fivetran relationship for implementation
  • Limited standalone documentation and community resources
  • May be overkill for simple batch replication needs
  • Competitive offerings provide more transparent per-connector pricing

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Fivetran HVR

On request

No published plan breakdown. See the Fivetran HVR 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 Fivetran HVR if

  • You need log-based change capture.
  • You work on Data Warehouse, Data Lake, Operational Databases.
  • You also want real-time replication.
Fivetran HVR review

Questions people ask

Is DuckDB or Fivetran HVR better?
Neither clearly leads. DuckDB starts at Free and Fivetran HVR at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or Fivetran HVR?
DuckDB has a free tier; the other does not. Paid plans start at Free for DuckDB and On request for Fivetran HVR.
Does DuckDB or Fivetran HVR run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. Fivetran HVR runs on Data Warehouse, Data Lake, Operational Databases.
Can I use DuckDB for free?
Yes. DuckDB has a free tier, so you can try it without paying. Fivetran HVR starts at On request.
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 Fivetran HVR is typically brought in for.
What can DuckDB do that Fivetran HVR cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. Fivetran HVR covers Log-based change capture, Real-time replication, Schema evolution handling, Multi-table consistency.

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.

Fivetran HVR: What databases does Fivetran HVR support?

HVR supports major databases including Oracle, SQL Server, PostgreSQL, MySQL, and others that emit transaction logs.

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.

Fivetran HVR: Is HVR part of standard Fivetran pricing?

Yes, HVR is integrated into Fivetran's usage-based pricing model with standard per-row-synced and transformation costs.

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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