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Databases · head to head

DuckDB vs Looker

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
Looker logo

Looker

Spreadsheets

Modern business intelligence platform by Google

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.; Looker no pricing published on website; quote-based model requires contacting Google Cloud sales
  • They diverge on capability: DuckDB covers In-process execution, Looker covers LookML Data Modeling.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and Looker actually diverge.

Attributes where DuckDB and Looker differ
AttributeDuckDBLooker
Starting priceFreeOn request
Pricing modelopen-sourceUnknown
Free tierYesNo
PlatformsLinux, macOS, Windows, WebAssemblyWeb, Cloud (Google Cloud Platform)
CategoryDatabasesSpreadsheets
Founded20192008

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 Looker

  • LookML Data Modeling
  • Embedded Analytics
  • API Access
  • Version Control
  • Data Actions
  • BigQuery
  • Snowflake
  • Redshift

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

Looker

  • Business intelligence and interactive dashboards for data-driven decision makingnot DuckDB
  • Embedded analytics for integrating BI capabilities into third-party applicationsnot 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.

Looker

  • No pricing published on website; quote-based model requires contacting Google Cloud sales
  • Pricing typically based on user count, deployment type, and feature requirements with no transparency

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Looker

On request

No published plan breakdown. See the Looker 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 Looker if

  • You need lookml data modeling.
  • You work on Web, Cloud (Google Cloud Platform).
  • You also want embedded analytics.
Looker review

Questions people ask

Is DuckDB or Looker better?
Neither clearly leads. DuckDB starts at Free and Looker at On request, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or Looker?
DuckDB has a free tier; the other does not. Paid plans start at Free for DuckDB and On request for Looker.
Does DuckDB or Looker run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. Looker runs on Web, Cloud (Google Cloud Platform).
Can I use DuckDB for free?
Yes. DuckDB has a free tier, so you can try it without paying. Looker 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 Looker is typically brought in for.
What can DuckDB do that Looker cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. Looker covers LookML Data Modeling, Embedded Analytics, API Access, Version Control.

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.

Looker: How much does Looker cost?

Looker does not publish pricing on its website. The platform uses a custom quote model where organizations contact Google Cloud sales for personalized pricing. Pricing is typically based on factors including user count, deployment type (cloud-hosted versus self-hosted), and required feature set.

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.

Looker: What are Looker's pricing tiers?

Looker offers subscription-based tiers typically including Standard with core BI capabilities, Advanced with enhanced features and integrations, and Premium with enterprise-grade features. Specific pricing and feature distinctions require contacting Google Cloud sales.

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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