Databases · head to head
CosmosDB vs DuckDB

CosmosDB
Databases
Globally distributed, multi-model database service from Azure
- From
- Free
- Rated
- -

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
- -
The short version
- Each has a real cost: CosmosDB autoscale provisioned throughput enforces a minimum of 1,000 RU/s, billed hourly whether or not the database is used; 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.
- They diverge on capability: CosmosDB covers Global Distribution, DuckDB covers In-process execution.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which CosmosDB and DuckDB actually diverge.
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 CosmosDB
- Global Distribution
- Multi-model APIs
- Elastic Scaling
- Five Consistency Levels
- SLA-backed Latency
- Automatic Indexing
- Serverless
- Azure Functions
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
What people use each for
The jobs each tool is most often brought in to do.
CosmosDB
- Running a globally distributed multi model database on Azurenot DuckDB
- Serving low latency reads and writes from multiple Azure regionsnot DuckDB
- Storing document, key value and graph data behind a managed servicenot DuckDB
DuckDB
- Transformation steps in a data pipeline that would otherwise need Spark, replaced by SQL over Parquet in a single processnot CosmosDB
- Analytical queries embedded in an application or a dashboard where shipping a database server alongside it is not acceptablenot CosmosDB
- Local exploration of files that are too large for a pandas dataframe but far too small to justify a warehousenot CosmosDB
- Continuous integration and testing of analytical SQL, where a real engine can run in the test process without provisioning anythingnot CosmosDB
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
CosmosDB
- Autoscale provisioned throughput enforces a minimum of 1,000 RU/s, billed hourly whether or not the database is used
- Provisioned throughput is charged in every region the account is replicated to, so multi region accounts multiply the RU bill
- Storage charges cover data, indexes and backups in each replicated region
- Egress out of Azure and between regions is charged, though ingress is free
- The free allowance is one account per Azure subscription, limited to 1,000 RU/s and 25 GB
- RU/s rates vary by region and are only shown through the pricing calculator rather than a flat published rate
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.
Pricing, plan by plan
CosmosDB
Free- Free TierFree
- 1000 RU/s
- 25GB storage
- First 12 months
- ServerlessFree
- Pay per request
- Auto-scaling
- Event-driven workloads
DuckDB
FreeNo published plan breakdown. See the DuckDB review.
Which should you pick?
Choose CosmosDB if
- You need global distribution.
- You want to start without paying.
- You work on Web, Azure.
- You also want multi-model apis.
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.
Questions people ask
- Is CosmosDB or DuckDB better?
- Neither clearly leads. CosmosDB starts at Free and DuckDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, CosmosDB or DuckDB?
- CosmosDB starts at Free and DuckDB at Free.
- Does CosmosDB or DuckDB run on more platforms?
- CosmosDB runs on Web, Azure. DuckDB runs on Linux, macOS, Windows, WebAssembly.
- Can I use CosmosDB for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is CosmosDB best used for?
- CosmosDB is most often used for running a globally distributed multi model database on azure, serving low latency reads and writes from multiple azure regions, storing document, key value and graph data behind a managed service. Of those, running a globally distributed multi model database on azure and serving low latency reads and writes from multiple azure regions are not what DuckDB is typically brought in for.
- What can CosmosDB do that DuckDB cannot?
- CosmosDB covers Global Distribution, Multi-model APIs, Elastic Scaling, Five Consistency Levels. DuckDB covers In-process execution, Vectorised columnar engine, Direct file querying, Zero dependencies.
Answered from the vendors’ own pages
CosmosDB: Is there a free tier for Azure Cosmos DB?
Yes, Cosmos DB offers a free tier with 1,000 RU/s of throughput and 25 GB of storage per month for the lifetime of the account, available to new accounts.
SourceDuckDB: 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.
CosmosDB: How is Cosmos DB priced after the free tier?
Cosmos DB uses three billing models: provisioned throughput billed per request unit per second, vCore pricing for certain APIs, or serverless consumption pricing where you pay only for requests processed. Reserved capacity offers 20% discount for one year or 30% for three years.
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.
CosmosDB: Can I change my pricing model after choosing one?
No. Once you select a compute pricing model and API, they cannot be changed. This choice is permanent for that database.
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.
CosmosDB: Is there a trial period for Cosmos DB beyond the free tier?
Azure offers a 30-day free trial account for all Azure services. Additionally, Azure AI customers may be eligible for a 90-day free Cosmos DB subscription through the Azure AI Advantage program.
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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