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Databases · head to head

DuckDB vs Glassbox

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
Glassbox logo

Glassbox

Business Intelligence

Digital experience intelligence

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.; Glassbox no fixed pricing tiers published; custom quotes required based on package, data retention, and session volume
  • They diverge on capability: DuckDB covers In-process execution, Glassbox covers Session Replay.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and Glassbox actually diverge.

Attributes where DuckDB and Glassbox differ
AttributeDuckDBGlassbox
Starting priceFreeOn request
Pricing modelopen-sourcesubscription
Free tierYesNo
PlatformsLinux, macOS, Windows, WebAssemblyWeb, Mobile, Hybrid
CategoryDatabasesBusiness Intelligence
Founded20192010

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 Glassbox

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

Glassbox

  • User experience analysisnot DuckDB
  • Bug reproductionnot DuckDB
  • Conversion optimizationnot DuckDB
  • Customer journey mappingnot DuckDB
  • Usability testingnot 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.

Glassbox

  • No fixed pricing tiers published; custom quotes required based on package, data retention, and session volume

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Glassbox

On request
  • CustomFree
    • Full Platform
    • Mobile 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 Glassbox if

  • You need session replay.
  • You work on Web, Mobile, Hybrid.
  • You also want struggle detection.
Glassbox review

Questions people ask

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

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.

Glassbox: How much does Glassbox cost?

Glassbox uses custom pricing based on three factors: the selected package (Production Operation, Marketing/Business, or Product), data retention period, and session volume. The vendor encourages contacting sales to build customized packages.

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.

Glassbox: Does Glassbox offer add-ons for specific industries?

Yes, Glassbox offers specialized add-on solutions including fraud prevention, accessibility features, and call center solutions tailored for financial organizations.

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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