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Databases · head to head

DuckDB vs Quantum Metric

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
Quantum Metric logo

Quantum Metric

Business Intelligence

Continuous product design platform

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.; Quantum Metric only enterprise plans are offered and the pricing page publishes no rate, no session volume tier and no minimum
  • They diverge on capability: DuckDB covers In-process execution, Quantum Metric covers Session Replay.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and Quantum Metric actually diverge.

Attributes where DuckDB and Quantum Metric differ
AttributeDuckDBQuantum Metric
Starting priceFreeOn request
Pricing modelopen-sourcesubscription
Free tierYesNo
PlatformsLinux, macOS, Windows, WebAssemblyWeb, Mobile
CategoryDatabasesBusiness Intelligence
Founded20192015

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 Quantum Metric

  • Session Replay
  • Opportunity Analysis
  • Anomaly Detection
  • Real-time Alerts
  • Impact Scoring
  • Adobe Analytics
  • Google Analytics
  • Salesforce

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

Quantum Metric

  • Session replay and digital experience analytics for large web and mobile propertiesnot DuckDB
  • Quantifying friction and conversion loss in checkout and signup flowsnot DuckDB
  • Streaming behavioural insights into a data warehousenot 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.

Quantum Metric

  • Only enterprise plans are offered and the pricing page publishes no rate, no session volume tier and no minimum
  • The page states plans are built around your business, with the only routes being a personalised discussion, a live demo or product tours
  • There is no self-serve tier, free plan or trial published

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Quantum Metric

On request
  • CustomFree
    • Full Platform
    • Real-time Analytics
    • Enterprise Support

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 Quantum Metric if

  • You need session replay.
  • You work on Web, Mobile.
  • You also want opportunity analysis.
Quantum Metric review

Questions people ask

Is DuckDB or Quantum Metric better?
Neither clearly leads. DuckDB starts at Free and Quantum Metric at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or Quantum Metric?
DuckDB has a free tier; the other does not. Paid plans start at Free for DuckDB and On request for Quantum Metric.
Does DuckDB or Quantum Metric run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. Quantum Metric runs on Web, Mobile.
Can I use DuckDB for free?
Yes. DuckDB has a free tier, so you can try it without paying. Quantum Metric 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 Quantum Metric is typically brought in for.
What can DuckDB do that Quantum Metric cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. Quantum Metric covers Session Replay, Opportunity Analysis, Anomaly Detection, Real-time Alerts.

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.

Quantum Metric: How much does Quantum Metric cost?

Quantum Metric uses custom pricing based on annual session volume, number of digital properties monitored, and product add-ons. Exact costs require contacting the sales team.

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.

Quantum Metric: Does Quantum Metric offer a free trial?

The pricing page does not mention a free trial option. Interested parties must request a demo to discuss pricing and obtain a custom quote.

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.

Quantum Metric: What factors affect Quantum Metric pricing?

Pricing scales with digital properties (websites and applications monitored), session volume (data collected and analyzed), and customer success tier selected. Add-on products like employee experience, data enrichment, and data streaming have separate pricing considerations.

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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