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Databases · head to head

DuckDB vs Firestore

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
Firestore logo

Firestore

Databases

Flexible, scalable NoSQL cloud database from Firebase

From
Free
Rated
-
Full reviewWebsite

The short version

  • 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.; Firestore the no-cost Spark plan caps Standard edition at 50,000 document reads, 20,000 writes and 20,000 deletes per day
  • They diverge on capability: DuckDB covers In-process execution, Firestore covers Document Model.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and Firestore actually diverge.

Attributes where DuckDB and Firestore differ
AttributeDuckDBFirestore
Pricing modelopen-sourcefreemium
PlatformsLinux, macOS, Windows, WebAssemblyWeb, Ios, Android, Flutter
Founded20192011

Identical on both: starting price (Free), free tier (Yes), 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 Firestore

  • Document Model
  • Real-time Updates
  • Offline Support
  • ACID Transactions
  • Expressive Queries
  • Multi-region
  • Security Rules
  • Firebase Auth

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

Firestore

  • Storing structured application data with realtime listenersnot DuckDB
  • Backing mobile and web apps with a serverless document databasenot DuckDB
  • Building offline first apps that sync when connectivity returnsnot 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.

Firestore

  • The no-cost Spark plan caps Standard edition at 50,000 document reads, 20,000 writes and 20,000 deletes per day
  • The Spark plan caps storage at 1 GiB and network egress at 10 GiB per month
  • Charging is per document read, so a query returning many documents bills for every one of them
  • Going beyond the free thresholds requires the pay as you go Blaze plan billed at Google Cloud rates with no fixed monthly ceiling

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

Firestore

Free
  • SparkFree
    • 1GB storage
    • 50K reads/day
    • 20K writes/day
  • BlazeFree
    • Pay as you go
    • Unlimited operations
    • Multi-region

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 Firestore if

  • You need document model.
  • You want to start without paying.
  • You work on Web, Ios, Android, Flutter.
  • You also want real-time updates.
Firestore review

Questions people ask

Is DuckDB or Firestore better?
Neither clearly leads. DuckDB starts at Free and Firestore at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or Firestore?
DuckDB starts at Free and Firestore at Free.
Does DuckDB or Firestore run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. Firestore runs on Web, Ios, Android, Flutter.
Can I use DuckDB for free?
Both have a free tier, so you can try either at no cost before committing.
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 Firestore is typically brought in for.
What can DuckDB do that Firestore cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. Firestore covers Document Model, Real-time Updates, Offline Support, ACID Transactions.

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.

Firestore: What are the free limits on Cloud Firestore?

The Spark Plan includes 1 GiB of stored data, 50,000 reads per day, 20,000 writes per day, and 20,000 deletes per day at no cost.

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.

Firestore: What happens when I exceed the Spark Plan free tier?

Exceeding the free tier requires upgrading to the Blaze Plan, which bills based on actual usage through Google Cloud pricing. Charges apply for reads, writes, deletes, and data storage.

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.

Firestore: Can I use Firestore without a credit card?

Yes, you can use the Spark Plan indefinitely without a credit card. To use the Blaze Plan (pay-as-you-go), a credit card is required.

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.

Firestore: Is there a trial period for Cloud Firestore?

No trial period is specified. The Spark Plan free tier serves as the trial, with no time limit.

Source
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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