Databases · head to head
DuckDB vs MotherDuck

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
- -

MotherDuck
Databases
Serverless analytics data warehouse built on DuckDB
- From
- Free
- Rated
- -
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.; MotherDuck the free Lite plan caps compute at 10 hours per month, which limits it to light or hobbyist workloads.
- They diverge on capability: DuckDB covers In-process execution, MotherDuck covers Serverless DuckDB instances.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which DuckDB and MotherDuck actually diverge.
| Attribute | DuckDB | MotherDuck |
|---|---|---|
| Pricing model | open-source | usage-based |
| Platforms | Linux, macOS, Windows, WebAssembly | web, api |
| Founded | 2019 | 2022 |
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 MotherDuck
- Serverless DuckDB instances
- Cloud storage querying
- MCP server
- Dives
- Flights
- Read-scaling replicas
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 MotherDuck
- Analytical queries embedded in an application or a dashboard where shipping a database server alongside it is not acceptablenot MotherDuck
- Local exploration of files that are too large for a pandas dataframe but far too small to justify a warehousenot MotherDuck
- Continuous integration and testing of analytical SQL, where a real engine can run in the test process without provisioning anythingnot MotherDuck
MotherDuck
- Ad-hoc analytics on gigabyte-to-terabyte datasetsnot DuckDB
- Querying data lake files in S3/GCS/Azure without ingestionnot DuckDB
- AI agent data analysis via MCPnot DuckDB
- Scheduled data pipeline transformationsnot 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.
MotherDuck
- The free Lite plan caps compute at 10 hours per month, which limits it to light or hobbyist workloads.
- Business plan usage charges on top of the $250/month base can make costs less predictable than flat-rate competitors.
- There are no academic or non-profit discounts, unlike some competing data platforms.
- Annual billing requires going through a sales conversation rather than a self-serve toggle.
Pricing, plan by plan
DuckDB
FreeNo published plan breakdown. See the DuckDB review.
MotherDuck
Free- LiteFree
- Up to 3 internal active users
- 2 service accounts
- 10GB free storage
- Business$250/month
- Up to 10 internal active users
- Unlimited service accounts
- 5 instance types with read-scaling replicas
- Enterprise$undefined/month
- Unlimited internal users and service accounts
- Fixed-cost capacity pricing
- AWS PrivateLink, IP allowlisting
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.
Choose MotherDuck if
- You need serverless duckdb instances.
- You want to start without paying.
- You work on web, api.
- You also want cloud storage querying.
Questions people ask
- Is DuckDB or MotherDuck better?
- Neither clearly leads. DuckDB starts at Free and MotherDuck at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, DuckDB or MotherDuck?
- DuckDB starts at Free and MotherDuck at Free.
- Does DuckDB or MotherDuck run on more platforms?
- DuckDB runs on Linux, macOS, Windows, WebAssembly. MotherDuck runs on web, api.
- 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 MotherDuck is typically brought in for.
- What can DuckDB do that MotherDuck cannot?
- DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies. MotherDuck covers Serverless DuckDB instances, Cloud storage querying, MCP server, Dives.
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.
MotherDuck: What does MotherDuck cost?
The Lite plan is free (up to 3 users, 10GB storage, 10 hours of Pulse compute/month). Business is $250/organization/month plus usage, with Enterprise available at custom fixed-cost pricing.
SourceDuckDB: 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.
MotherDuck: Is there a free plan and what are its limits?
Yes, the Lite plan is free for up to 3 internal active users and 2 service accounts, with 10GB of storage and 10 hours of Pulse compute per month.
SourceDuckDB: 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.
MotherDuck: How is usage metered?
Compute instances (Pulse, Standard, Jumbo, Mega, Giga) are billed per second at hourly rates from $0.60 to $24.00/hour, storage is $0.04/GB-month, and AI Functions cost $1.00 per AI Unit.
SourceDuckDB: 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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