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Databases · head to head

DuckDB vs MongoDB

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
MongoDB logo

MongoDB

Technology

The developer data platform

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.; MongoDB 16 MB maximum document size limits large single objects
  • They diverge on capability: DuckDB covers In-process execution, MongoDB covers Document model.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which DuckDB and MongoDB actually diverge.

Attributes where DuckDB and MongoDB differ
AttributeDuckDBMongoDB
Pricing modelopen-sourceUnknown
PlatformsLinux, macOS, Windows, WebAssemblyCloud (Atlas), Self-hosted, Multi-cloud (AWS, Google Cloud, Azure)
CategoryDatabasesTechnology
Founded20192007

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

  • Document model
  • Distributed architecture
  • ACID transactions
  • Real-time analytics
  • Full-text search
  • Time series data
  • Geospatial queries
  • Aggregation framework

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

MongoDB

  • Mobile applicationsnot DuckDB
  • Content managementnot DuckDB
  • Real-time analyticsnot DuckDB
  • IoT applicationsnot DuckDB
  • Gaming backendsnot 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.

MongoDB

  • 16 MB maximum document size limits large single objects
  • No native JOIN support for relational data operations
  • Higher memory usage due to storing field names with each document
  • Eventual consistency in distributed deployments can cause data stale reads

Pricing, plan by plan

DuckDB

Free

No published plan breakdown. See the DuckDB review.

MongoDB

Free
  • M0Free
    • 512 MB storage
    • Learning and exploration
  • M2$9/month
    • 2 GB storage
    • Development and testing
  • M5$25/month
    • 5 GB storage
  • M10+$56.94/month
    • Dedicated clusters for production

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 MongoDB if

  • You need document model.
  • You want to start without paying.
  • You work on Cloud (Atlas), Self-hosted, Multi-cloud (AWS, Google Cloud, Azure).
  • You also want distributed architecture.
MongoDB review

Questions people ask

Is DuckDB or MongoDB better?
Neither clearly leads. DuckDB starts at Free and MongoDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, DuckDB or MongoDB?
DuckDB starts at Free and MongoDB at Free.
Does DuckDB or MongoDB run on more platforms?
DuckDB runs on Linux, macOS, Windows, WebAssembly. MongoDB runs on Cloud (Atlas), Self-hosted, Multi-cloud (AWS, Google Cloud, Azure).
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 MongoDB is typically brought in for.
What can DuckDB do that MongoDB cannot?
DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. MongoDB covers Document model, Distributed architecture, ACID transactions, Real-time analytics.

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.

MongoDB: Does MongoDB offer a free tier?

Yes. MongoDB Atlas offers an M0 free tier with 512 MB storage for learning and exploration, plus paid options starting at $9/month for M2 with 2 GB storage.

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.

MongoDB: Can I self-host MongoDB?

Yes. You can run MongoDB Community Edition on your own servers, or use MongoDB Enterprise Advanced for self-managed production deployments with enterprise features.

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.

MongoDB: What is the maximum document size in MongoDB?

Documents are limited to 16 MB. For documents exceeding this limit, you can use MongoDB's GridFS API to store files larger than the maximum size.

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.

MongoDB: Does MongoDB support ACID transactions?

Yes. MongoDB supports ACID transactions within a single document by default, and multi-document ACID transactions are available for replica sets and sharded clusters in MongoDB 4.0+.

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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